(Luận văn thạc sĩ) impact of communication in agile development on the performance of engineers in semiconductor industry

INTRODUCTION

Background of the research

The semiconductor industry is a crucial growth sector in the global economy, supplying essential components for various products, including mobile phones, telecommunications equipment, robotics, and aerospace Despite a forecasted decline of approximately 11.2% in worldwide semiconductor sales due to the global economic downturn, a rebound is expected with an 18.5% increase in 2024 This industry is marked by rapid technological advancements and a high level of specialization, involving complex manufacturing processes that demand significant investment in research and development Additionally, it is characterized by intense competition among companies striving for market share and innovation in product development.

The semiconductor industry is classified as the heart of the transformation of advanced economies and agile manufacturing has been recognized as a strategy for achieving sustainable competitiveness (Lee et al., 2005)

The semiconductor industry is primarily divided into three business models: fabless companies, foundries, and integrated device manufacturers (IDMs) Foundries specialize in chip fabrication without design capabilities, while IDMs manage the entire supply chain, including design, manufacturing, and sales of integrated circuit (IC) products In contrast, fabless companies focus on designing and developing semiconductor products, outsourcing manufacturing to third-party firms, with their main objectives centered on innovation and differentiation.

This article explores the journey of a fabless company based in Vietnam, established in 2004, with its headquarters in the US and additional offices globally The Vietnam office specializes in designing power integrated circuits (ICs) for various industries, including mobile phones, telecommunications, and medical instruments, boasting a product range of millions of modules To enhance competitiveness, the company emphasizes creativity and innovation Initially utilizing the waterfall method for project management, they have since transitioned to agile methodologies, fostering collaboration within co-located teams and shared office spaces Due to confidentiality concerns, internet access is restricted for all computers, and peripheral devices are limited.

The company utilizes a LAN network for efficient information management, employing various communication channels such as face-to-face interactions, local chat through team platforms, email, and occasional video conferences for design reviews This setup creates an optimal environment for implementing agile development practices, which offer substantial advantages to the software industry.

Effective communication is crucial in R&D projects, particularly in the semiconductor industry, where design managers hold differing views on the impact of standing meetings on engineer performance While some managers worry that frequent stand-ups may hinder creativity and task completion, others advocate for proactive communication to enhance team engagement and project outcomes Recognizing the importance of communication, the office director aims to investigate its effects on engineers' performance, prompting the authors to explore management challenges within the industry.

Agile development, which originated with The Agile Manifesto in 2001, has transcended the software industry and gained traction in various sectors, including the development of physical products like consumer electronics and medical devices Defined by its ability to quickly respond and adapt in dynamic environments, agile contrasts with the linear waterfall methodology, which is suited for projects with clearly defined outcomes Agile methodology embraces flexibility, allowing for late-stage directional changes and prioritizing stakeholder feedback throughout the development process Additionally, research by Cooper & Sommer (2016) highlights that agile development aligns with evolving customer needs, resulting in enhanced implementation, faster development cycles, and improved team communication.

Communication is the process of transferring information from a sender to a receiver, which must be understood by the receiver (Koontz & Henrich, 1986) Various communication media, including face-to-face communication (FTFC), computer-mediated communication (CMC), and mobile-mediated channels, facilitate this exchange Robbins and Judge (2019) emphasized that effective communication involves both the transfer and comprehension of meaning At the organizational level, Kalogiannidis (2021) highlighted the critical role of communication in enhancing performance and growth, while Bucăţa and Rizescu (2017) noted that it serves as a management tool that strengthens interpersonal relationships and fosters a supportive internal environment Furthermore, Alan and Susan (1998) found that utilizing richer communication mediums improves team performance On an individual level, a higher ratio of mediated communication compared to face-to-face interactions positively influences individual creativity (Thatcher & Brown, 2010).

Engineers represent a unique occupational group, blending elements of professionalism within a field that doesn't fit the traditional definition of a profession (Bigliardi et al., 2005) In organizations, they play a crucial role by applying their technical expertise to develop structures, products, and processes that significantly benefit both the organization and its clients (Bayan Salim Al-Numan, 2019) Their responsibilities include new product development, enhancing existing products through maintenance and improvements, and designing systems to boost organizational efficiency The performance of research and development (R&D) engineers is notably different from that of other staff members, as it cannot solely be assessed by the quantity and quality of work produced (Clarke, 2002; Lee & Allen, 1982; Allen et al., 1980) This research will focus on evaluating R&D engineers' performance based on creativity and task execution, which are key indicators of their contributions (Min-Peng & Xiao-Hu, 2012).

Research motivation

In the era of the Fourth Industrial Revolution, semiconductors are becoming essential as we adopt innovative applications across multiple sectors, including smart vehicles, advanced manufacturing, artificial intelligence, data centers, and robotics This growing reliance on technology is driving a consistent increase in semiconductor demand.

The semiconductor industry is facing an urgent need for smarter and smaller technologies, prompting enhancements in both product development and manufacturing capabilities to keep pace with the ongoing revolution.

The rise of remote work has prompted organizations worldwide to embrace new communication tools, significantly enhancing productivity Notably, Zoom's revenue surged to $4.3 billion in 2021, boasting 213,000 enterprise customers by 2022, while Microsoft Teams experienced an impressive 894% growth, reaching 270 million users in the same year However, operating effectively in a decentralized environment can pose challenges, particularly in creative fields like Research & Development, highlighting the need to analyze how various communication mediums impact employee performance.

A report by Jones and Ghosh (2016) highlights that semiconductor CFOs recognize the competitive advantages gained through the integration of agile development and data analysis in their R&D processes, leading to faster time to market, improved ROI on R&D expenditures, and enhanced productivity Evidence indicates a growing number of semiconductor companies adopting agile methodologies and reaping substantial benefits Furthermore, effective communication and collaboration are critical success factors in agile projects (Chow & Cao, 2008; Ahimbisibwe et al., 2013; Van Kelle et al., 2015; Nguyen, 2016) Given the communication challenges noted in fabless companies and the unique dynamics of the semiconductor industry, it is essential for management to explore how communication mediums influence staff performance to establish an effective communication process.

Agile development has become increasingly popular and effective in the software industry over the past two decades (Mehta & Sood, 2023; Shrivastava, 2010; Erickson et al., 2005) While there is a wealth of scholarly research on communication within agile development for software, there is a notable lack of studies focused on the semiconductor industry As the significance of agile practices and communication strategies continues to rise, it is essential to explore their application in the semiconductor sector.

One of the key principles of the Agile Manifesto emphasizes the importance of prioritizing individuals and interactions over processes and tools (Beck et al., 2001) Additionally, agile methodology posits that face-to-face conversations are the most efficient and effective means of information exchange within a development team This principle is supported by media richness theory (Lengel & Daft, 1984), which indicates that in-person communication offers a greater level of richness and effectiveness compared to other communication methods.

Agile methodologies prioritize direct interactions to boost collaboration, understanding, and quick decision-making within development teams (Yu & Petter, 2014; Lindvall, 2002) Suh (1999) highlighted that critical mass theory and media richness theory illustrate the influence of various communication media on task performance, underscoring the importance of effective communication in achieving project goals.

Brown (2010) established that mixed media communication enhances individual creativity, yet previous studies primarily addressed the R&D process and performance in general, without specifically examining engineers' creativity and task performance in a unified context Consequently, there is a need for research that investigates the effects of communication on engineer performance within semiconductor companies employing agile development methodologies in their R&D processes.

In high-tech organizations, creativity is shaped by a six-structural model encompassing work atmosphere, vertical collaboration, autonomy, respect, alignment, and lateral collaboration (Lapierre & Giroux, 2003) Research by Dul et al (2011) indicates that the social organizational context significantly influences individual creativity, outweighing the effects of the physical environment, though the latter still plays a role Amabile & Pillemer (2012) further emphasize the importance of the social environment in fostering creativity and advocate for the evaluation of physical factors on individual creative output.

So, It is necessary to study communication medium as a physical working environment on individual’s creativity in term of engineers in semiconductor industry

Employee agility is a crucial success factor in adopting agile development, as emphasized by Chonko and Jones (2005), who argue that a firm cannot effectively transform to agile practices without addressing workforce agility According to Sherehiy, employee agility encompasses three key dimensions: proactivity, adaptability, and resilience.

A proactive personality significantly contributes to resource accumulation for creativity, as highlighted by Gong et al (2010) This underscores the importance of examining how employee agility, as a skill beyond domain-specific expertise, impacts individual performance.

Considering the aforementioned reasons and principles, conducting research to explore the impact of communication on engineers' performance becomes crucial from a theoretical perspective h

Research Objectives and research question

This study aims to investigate the effects of communication mediums, specifically Face-to-Face Communication (FTFC) and Computer-Mediated Communication (CMC), on engineers' performance regarding creativity and task execution The findings provide valuable insights for managers in choosing the most effective communication methods within their organizations, particularly in the semiconductor sector.

Adopting agile development practices in the semiconductor industry significantly enhances workforce agility, which is crucial for fostering innovation This study highlights how employee agility serves as a moderating factor that influences the relationship between communication media and engineers' creativity Additionally, it underscores the direct effects of employee agility on both engineers' creativity and their task performance, emphasizing its importance in driving industry advancements.

Three research questions (RQ) were developed based on the objectives:

RQ1: Does communication medium in agile development affect to engineers’ performance in the semiconductor industry?

RQ2: Does employee agility impact engineer performance in the semiconductor industry?

RQ3: Does employee agility influence the relationship of communication medium on engineers' performance?

This research aims to survey engineers involved in the design processes of semiconductor companies utilizing modern technology and communication tools The objective is to assess how communication influences engineer performance during development Ultimately, the study seeks to provide managers with actionable recommendations to minimize communication barriers and enhance engineers' productivity.

Research’s scope

The study focuses on four key aspects: communication in agile development, engineer performance, and the time frame of the research, which spanned from December 19th to May 20th It encompasses fabless companies and design centers within and outside Vietnam, specifically targeting R&D engineers in the semiconductor industry.

Research findings

This study highlights the importance of effective communication mediums in enhancing engineers' performance, particularly in the semiconductor industry It reveals that employee agility significantly influences the success of agile development, as it positively affects both creativity and task performance among engineers Additionally, employee agility plays a crucial role in moderating the relationship between computer-mediated communication (CMC) and engineers' creativity.

The research findings highlight the significance of academic support by endorsing two key theories Firstly, the component of creativity theory (Amabile, 2012) illustrates that employee agility, characterized by the domain-relevant skills of agile engineers, is integral to creative processes within Computer-Mediated Communication (CMC) Secondly, the AMO theory positions employee agility as an essential element of ability (A), reinforcing individual performance and contributing to overall effectiveness in the workplace.

Thesis structure

The article is structured into six chapters, beginning with Chapter 1, which outlines the motivation, rationale, goals, and scope of the study Chapter 2 presents a thorough literature review to establish theoretical foundations, develop hypotheses, and create a conceptual model for testing In Chapter 3, the study details the formulation of hypotheses and the research model Chapter 4 explains the research methodology, covering questionnaire design, data collection, and data processing techniques Chapter 5 analyzes the data and presents the results, including the sample profile Finally, Chapter 6 discusses the findings, addresses research questions, and offers implications and suggestions for future research.

LITERATURE REVIEW

Theories background

In 1984, Richard L Daft and Robert H Lengel introduced the Media Richness Theory (MRT), highlighting face-to-face communication as the most effective medium for facilitating natural exchanges MRT identifies four key components that determine the richness of a communication medium: immediate feedback, multiple cues, language variety, and personal focus (Kumi Ishii et al., 2019) The theory suggests that task performance improves when the media richness aligns with the information needs of the task For instance, rich mediums like face-to-face meetings are ideal for ambiguous tasks with multiple interpretations, while lower-rich mediums, such as computer-mediated communication, are better suited for straightforward tasks that may lose information An enhancement of MRT includes examining the message valence to select the appropriate communication channel.

In 1999, Dennis and Valacich introduced Media Synchronicity Theory (MST) at the Hawaii International Conference on System Sciences, emphasizing that richer communication media do not always enhance performance, particularly in tasks with high equivocality MST posits that the effectiveness of communication is influenced not just by media richness but also by its alignment with task requirements For tasks characterized by greater equivocality, which demand extensive information processing and coordination, media that provide higher synchronicity, such as real-time communication, can be more effective than richness alone.

Media Synchronicity Theory (MST) explores the intricate relationship between media selection, task characteristics, and performance results, as highlighted by Denis et al (2008) It contests the belief that richer media consistently enhance performance in tasks with greater ambiguity The core emphasis of MST is on the effectiveness of media in fostering synchronicity, which enables coordinated expression among individuals working collaboratively.

Carlson and George (2004) highlighted that media synchronicity plays a crucial role in assisting managers with media selection for communication Additionally, Limayem et al (2007) examined how varying transmission velocities impact team collaboration, discovering that higher velocity media, like instant messaging, enhance information exchange and decision-making, ultimately boosting task performance.

According to Dennis et al (2008), synchronous media, including face-to-face meetings and videoconferencing, are more effective for convergence processes that demand rich interaction and immediate feedback The Media Synchronization Theory (MST) further suggests that communication comprises two essential processes: conveyance and convergence.

Figure 2 1: Media Synchronicity Theory (Adopted from A Dennis et al., 2008)

The conveyance process entails delivering diverse new information, equipping the receiver with essential and relevant details to aid in forming and adjusting their mental understanding of the situation.

Convergence processes refer to pre-processed information before individual's translation of a given situation rather than the information in nature itself (Denis at al.,

Convergence focuses on validating or slightly modifying existing mental models, often requiring less information processing than conveyance processes According to Media Synchronicity Theory (MST), communication effectiveness improves when the needs of both conveyance and convergence align with appropriate media that offer essential attributes like speed, parallelism, symbol sets, repeatability, and processability Consequently, enhancing communication performance is achievable by employing a variety of media for tasks instead of depending on just one medium.

The Componential Theory of Creativity, developed by Teresa Amabile in 1996, outlines a model comprising three essential variables: domain-relevant skills, creativity-relevant skills, and intrinsic task motivation According to Amabile and Pillemer (2012), creativity is defined as the ability to generate novel ideas or solutions that are appropriate for specific objectives This theory highlights four key elements necessary for creative responses: the individual's domain-relevant skills, creativity-relevant processes, intrinsic motivation, and the social environment in which the individual operates.

Research indicates that both social and physical environments significantly impact individual creativity Factors such as colleague support, resource availability, and organizational culture play a vital role in fostering creativity (Paulus & Dzindolet, 2008; Erez & Nouri, 2010; Belias & Koustelios, 2014) Additionally, the design of creative workplaces and the quality of working facilities are also crucial (Mitchell & Gary, 2002; Jan Dul et al., 2011; Richardson & Mishra, 2018) Amabile and Pillemer (2012) emphasize the importance of the social environment in influencing creativity and advocate for assessing the physical workspace's effects on creative output.

2.1.3 Ability, Motivation, and Opportunity (AMO) theory h

The Ability-Motivation-Opportunity (AMO) theory is a key framework in organizational behavior that explains the factors affecting both individual and collective performance (Bos‐Nehles, 2013) Introduced by Jeffrey Pfeffer and John F Veiga in 1999, the theory asserts that an individual's performance (P) is determined by their ability (A), motivation (M), and opportunities (O) (Kellner et al., 2019) Since its development in 2000, the AMO framework has gained widespread acceptance for clarifying the relationship between performance and human resource management (Appelbaum et al., 2000; Boxall & Purcell, 2003; Marin-Garcia & Tomas, 2016) Moreover, a lack of suitable opportunities in the work environment can diminish the significance of motivation and abilities.

The AMO model highlights the behavioral mechanisms connecting human resource management (HRM) initiatives to performance enhancements However, employees' skills and motivation can be rendered ineffective if the work environment does not offer adequate opportunities for growth and development.

Communication

Communication is the exchange of information through verbal and nonverbal channels between a sender and a receiver As highlighted by Stephen P Robbins in "Organizational Behavior," communication serves five essential functions within a group or organization: management, feedback, emotional sharing, persuasion, and information exchange The management function specifically involves coordinating individual efforts to achieve organizational goals.

Effective communication is essential for achieving organizational goals, as it encompasses various elements such as feedback, emotional sharing, persuasion, and information exchange Feedback provides critical insights into performance, while emotional sharing allows individuals to express their feelings related to work Persuasion is utilized to influence attitudes and behaviors, and information exchange facilitates the transfer of knowledge within an organization or between firms In today's landscape, communication occurs through diverse mediums, enhancing the way information is shared and understood.

2005; Livingstone, 2002; Nguyen et al., 2020), even multi mediums outside face-to-face communication, such as mobile-mediated communication medium, computer-mediated mediums, and social media communication medium

Effective organizational communication is a complex and ongoing process through which members interact verbally, non-verbally, electronically, and in writing This interaction involves stakeholders both internally and externally, aiming not only to inform employees about tasks and organizational policies but also to foster and nurture a cohesive internal community.

Team communication, also known as small group communication (Harris & Sherblom,

Team communication is a dynamic process where group members engage in symbolic behaviors to create a shared understanding and achieve common goals (Harris & Sherblom, 2018; Marlow, 2018) This ongoing interaction occurs over time and is essential for effective teamwork (Thomas E & John C, 2018) Various definitions and assessments of team communication often fail to align with the concept of information sharing, which is evaluated based on aspects like clarity, frequency of interaction, and knowledge sharing (Lawson et al., 2009) Recognized as a critical component of team processes, effective communication fosters interdependent behaviors that enhance performance outcomes (Hirst & Mann, 2004) Additionally, it allows team members to gather vital information about environmental and situational factors that influence their tasks (Marks et al., 2001; MacMillan et al.).

Effective communication between managers and employees is essential for reducing uncertainty and fostering clarity in the workplace By delivering accurate and useful information, managers help employees understand their tasks and associated expectations Moreover, strong communication allows employees to gain insights into organizational policies and practices, as well as the rationale behind decisions and procedures.

In 1991, a new perspective on communication efficiency was introduced, focusing on the importance of reducing communication costs and efforts This approach highlighted that effective communication involves engaging in diverse methods that prioritize high speed and low resource expenditure, including both financial costs and effort.

In summary, communication is the lifeblood of an organization (Sethi & Seth, 2009), and communication effectiveness refers to achieving the intended purpose of the communication in the best possible manner

In agile development, effective communication is crucial for exchanging information among stakeholders and sharing knowledge within the team (Cooper & Sommer, 2016) Its primary goal is to swiftly adapt to unforeseen changes during the development process (Cho et al., 1996) Agility in software development hinges on the team's ability to incorporate user-requested changes efficiently throughout the project life cycle (Lee & Xia, 2010) The success of agile methodologies is closely tied to strong communication among team members (Lindvall et al., 2002) As agile methods demand faster development (Cooper & Sommer, 2018), enhancing communication efficiency is essential for achieving higher agility (Lee & Xia, 2010) Consequently, the choice of communication mediums significantly influences project outcomes.

The Agile Manifesto emphasizes face-to-face communication as a crucial channel for effective collaboration Research supports the value of daily standup meetings as a form of this communication (Viktoria Stray et al., 2016) However, the COVID-19 pandemic posed significant challenges, preventing teams from gathering in person (Mancl & Fraser, 2020) In response, Agile teams have adapted by leveraging various communication methods, including emails, instant messaging, and collaborative platforms, each with its unique advantages and limitations (Pikkarainen et al., 2008; Alzoubi, 2016) Selecting the right communication channel is essential for fostering collaboration, as Agile principles advocate for close cooperation between business stakeholders and developers, highlighting the necessity of daily interactions.

Empirical research and the DSDM Project Framework emphasize the importance of sharing project information through informal, face-to-face conversations instead of relying solely on documentation However, challenges arise with larger teams, as effective communication becomes more difficult (Lindvall et al., 2002) For optimal collaboration and knowledge exchange, it is recommended that team sizes be kept to no more than 12 members (Beck et al., 2001; Lindvall, 2002; Cohen et al., 2004) Additionally, maintaining active communication is particularly challenging for geographically dispersed agile teams (Alzoubi, 2016) Utilizing agile enterprise architecture can significantly improve communication and enhance overall performance in such distributed environments.

Face-to-face communication (FTFC)

Face-to-face communication (FTFC) is a direct form of social interaction that occurs without the use of technology (Crowley & Mitchell, 1994) Despite predictions of its decline due to digital advancements (Van der Kleij et al., 2009; Drago, 2015), research by H Bathelt and P Turi (2011) emphasizes that FTFC remains a valuable medium, particularly in contexts requiring agility FTFC fosters essential social elements such as touch, shared activities, and informal interactions (Nardi & Whittaker, 2002) In organizational settings, it is consistently recognized as the most effective way to communicate information between staff (Ean, 2010; Kirkman et al., 2004) Studies indicate a positive link between productivity and the focused use of time and energy in critical areas, particularly in group problem-solving and meetings with senior management (Wu, 2008), highlighting the importance of making FTFC a regular practice.

Knowledge Sharing, FTFC and Labour Productivity

"Knowledge sharing" often refers to the various methods of transferring knowledge, including both one-way and two-way exchanges (Murray & Peyrefitte, 2007) However, the term is frequently used imprecisely.

"knowledge sharing" is specifically used in the context of work, it pertains solely to those instances of knowledge exchange that occur in this setting (Cummings, (2003)

The impact of direct voice practices on organizational productivity remains ambiguous (Bryson, 2006; Estell, 2021) In the absence of counterbalancing forces like union representation, employees may lack motivation to suggest productivity improvements, fearing they won't receive a fair share of the benefits (Freeman & Medoff, 1984) Additionally, communication barriers can arise when employees voice concerns through representatives, potentially hindering effective dialogue between management and staff (Pfeffer, 1994; Storey, 1992) Conversely, direct voice mechanisms can help managers address the diverse needs of their workforce, fostering increased cooperation and commitment (White & Bryson, 2013) However, substantial evidence linking direct voice practices to productivity is still lacking Face-to-face communication (F2F) is essential for team tasks, particularly in complex R&D environments, where prior research indicates that F2F interaction is superior for non-routine tasks fraught with uncertainty (Bordia, 1997; Chao et al., 2020) This mode of communication effectively conveys intricate, context-specific information vital for knowledge advancement and technological innovation (Tushman, 1979; Santoro & Saparito, 2003).

Computer-mediated communication (CMC) encompasses interactions that occur via digital platforms such as instant messaging, email, chat rooms, online forums, and social networks (Yao & Ling, 2020; Xiaojuan et al., 2013; Herring, 2010) These technologies enable individuals to exchange messages, information, and ideas effectively Additionally, CMC has evolved to include text-based communication methods like text messaging (Tomic et al., 2004) According to McQuail (2005), CMC is defined as any form of human interaction facilitated by two or more electronic devices.

Computer-mediated communication (CMC) tools facilitate collaboration and communication across distances, enabling virtual meetings and instant messaging for agile teams to work together effectively However, the lack of nonverbal cues, such as facial expressions and body language, can hinder effective communication, leading to misunderstandings, diminished trust, and challenges in accurately conveying emotions and context.

Computer-mediated communication (CMC) is defined as the process through which individuals create, exchange, and perceive information via networked telecommunications systems, which enable the encoding, transmission, and decoding of messages (O’Malley et al., 1996) It serves as more than just a tool; it represents a fusion of technology, medium, and the foundation of social relationships (Tu, 2000; Beka, 2005; Sherblom, 2010) CMC integrates social interactions with the environments in which they occur and the tools utilized by individuals to navigate those spaces.

Engineers performance

Performance is defined as "behavior that has been evaluated in terms of its contribution to the organization's goals" (Walker et al., 1979) Engineers, as the specialized workforce of a company, play a crucial role in driving innovation (Menzel et al., 2007) Effectively measuring and managing the performance of engineers is vital within the R&D process (Werner & Souder, 1997) Evaluating the performance of R&D engineers necessitates a distinct approach compared to general staff due to the unique nature of their work (Thamhain, 2003; Brown & Svenson, 1998) A key output of the R&D department includes the development of new products and features, which requires engineers to generate a higher volume of ideas, serving as a foundation for creativity alongside completing their tasks (Gerstberger, 1968).

Base on scholars, there are several differences in task performance and creativity performance as follows

Table 2 1: Review on the description of task performance and creativity

Authors Task performance Creativity performance

Task performance represents the fulfillment of expected job responsibilities

Creativity performance refers to the generation of unique and unconventional ideas that contribute to innovation and problem-solving

Task performance is about following established procedures and meeting predefined standards

Creativity performance involves breaking from traditional approaches and introducing new and inventive solutions

Task performance is concerned with known and well-defined job requirements

Creativity performance involves exploring new possibilities and generating original contributions to enhance organizational outcomes

Task performance is primarily concerned with the effective and efficient execution of assigned job tasks

Creativity performance involves the generation of original and valuable ideas that go beyond routine job requirements

According to Wang (2013), the effectiveness of R&D engineers is influenced by four key factors: creativity, task performance, altruism toward colleagues, and conscientiousness However, given the unique nature of their roles, creativity and task performance emerge as the primary indicators of their success Therefore, this thesis will concentrate on these two critical aspects.

- Task performance refers to performance on core tasks defined and assigned by a supervisor or by the employer that meet

- Creativity is defined as products, ideas, or procedures that are original and potentially useful to an organization (Amabile, 1988; Oldham & Cummings, 1996) h

In R&D organizations, engineers are the key workforce and essential drivers of creativity and innovation, significantly enhancing business value Creativity is viewed from various perspectives; Amabile (1988) defines it as creating products or services that are both unique and beneficial to the organization, while Woodman et al (1993) describe it as the collaborative development of valuable and practical new ideas or processes within a complex social system Individual creativity is further supported by access to resources such as funding, materials, facilities, and information, which play a crucial role in fostering innovation.

According to Amabile (1997), creativity in individuals is determined by the combination of expertise, creative thinking skills, and motivation In an organizational context, creative individuals contribute valuable ideas that enhance products, practices, and procedures (Gilson & Shalley, 2004) Consequently, the creativity of engineers plays a crucial role in enabling organizations to effectively respond to business demands.

Task performance is essential for both individual and organizational success, as it encompasses the effective execution and completion of job-related duties and responsibilities by employees.

Understanding the factors that influence task performance is crucial for organizations aiming to enhance productivity and meet their objectives Task performance refers to how effectively individuals carry out the specific activities and responsibilities associated with their job roles (Motowidlo & Van Scotter, 1994) It encompasses the proficiency demonstrated in fulfilling core job duties and responsibilities required for a particular position (Mount et al., 1994) Essentially, task performance is synonymous with in-role performance, reflecting the level of achievement related to assigned job duties (Williams & Anderson, 1991).

Employee agility

Since 2008, Sherehiy has emphasized that employee agility refers to the capacity to respond and adapt to unpredictable and rapidly changing environments effectively Subsequent research by Alavi (2016) and Cai et al (2018) has further defined employee agility as the ability to react promptly and effectively to sudden organizational changes This concept encompasses not only timely responses to unforeseen shifts but also the capability to leverage these changes as opportunities for innovation and the acquisition of new technologies (Bathaei et al., 2019; Chonko & Jones, 2005).

Employee agility encompasses three key dimensions: proactivity, adaptability, and resilience, which are essential for enhancing organizational performance (Alavi, 2016; Cai et al., 2018; Muduli, 2017; Pitafi, Liu, & Cai, 2018) Research indicates that fostering employee agility leads to significant benefits, including improved learning systems, enhanced learning capacity, higher product quality, and increased customer satisfaction (Alavi, 2016; Pitafi et al., 2019).

Individual agility, or employee agility, is the capacity to think creatively and adapt to unforeseen situations by developing innovative solutions to overcome challenges or seize opportunities This skill necessitates a keen awareness of the current environment and the ability to anticipate changes, enabling individuals to respond promptly and effectively when circumstances demand it.

Research gaps

This study identifies key research gaps in the influence of communication on employee performance, particularly within the semiconductor industry utilizing agile development It will explore the impact of various communication mediums on engineers' creativity and task performance, which are critical indicators for R&D engineers Additionally, the research will assess the role of employee agility in enhancing individual performance and its significance in the relationship between communication and engineers' performance in an agile context.

HYPOTHESIS DEVELOPMENT AND CONCEPTUAL MODEL

Communication and engineer’s performance

According to research question 01, the below hypotheses will be developed base on communication and engineer performance specifically focus on communication medium influences engineer’s creativity and their task performance

3.1.1 Face-to-face communication and engineers’ performance

The AMO model, as outlined by Cummings and Schwab (1973), emphasizes that employee performance is driven by three key elements: ability (A), motivation (M), and opportunities (O) Opportunities, as defined by Boxall and Purcell (2003), encompass the environmental and contextual factors that can either facilitate or obstruct employee performance Furthermore, effective communication and informal sharing are recognized as significant opportunities that can enhance performance (Marin-Garcia).

& Tomas 2016) for employees to engage in direct, in-person interaction with others So, communication has an impact on individual performance

Creativity is not solely an individual process but emerges from interactions with others, as suggested by Csikszentmihalyi (1996) Effective communication significantly enhances individual creativity, promoting the exchange of ideas and fostering innovation (Lee & Kim, 2021) Increased interaction leads to a greater quantity and quality of novel concepts (West, 1990) Allen (1977) emphasizes the importance of face-to-face communication among engineers and technologists for effective information exchange, a notion supported by the Media Richness Theory (MRT), which states that face-to-face communication provides the richest information (Suh, 1999) This richness is attributed to the ability to perceive verbal cues, gestures, and emotions during interactions Consequently, as the quantity and quality of information improve, so does decision-making effectiveness (Keller & Staelin, 1987) Moreover, face-to-face communication plays a crucial role in building social relationships (Drago, 2015; Flaherty et al.).

1998) to facilitate individual creativity Hence, the following hypothesis is formed:

H1a: Face-to-face communication has a positive impact on engineers’ creativity in the semiconductor industry

H1b: Face-to-face communication has a positive impact on engineers’ task performance in the semiconductor industry

3.1.2 Computer-mediated communication and engineers’ performance

According to AMO theory, communication significantly impacts individual performance (Marin-Garcia & Tomas, 2016), with human brains being more effective in face-to-face communication (Kock, 2007) Amabile’s creativity theory identifies four components that influence individual creativity, highlighting the role of intrinsic task motivation, which is enhanced by computer-mediated communication (CMC) (Chang & Wang, 2008; Spitzberg, 2006; Hoffman & Novak, 1996) Additionally, CMC fosters independent work, allowing individuals to generate more ideas compared to collaborative efforts (Mullen et al., 1991; Paulus et al., 1995) Thus, there is a clear connection between CMC and enhanced individual creativity.

Computer-mediated communication (CMC) serves as an essential tool that enhances the working environment through its modern and appealing interface According to Amabile (2012), the physical workspace significantly influences individual creativity, highlighting the need for further research in this area Consequently, the integration of CMC within the workplace fosters creativity by improving the overall work atmosphere.

Brainstorming is a recognized group technique that fosters creativity and idea generation (Suleiman & Watson, 2008) Additionally, Computer-Mediated Communication (CMC) functions as a supportive system for electronic brainstorming (Michinov & Primois, 2005), effectively engaging with various elements of creativity theory.

A study by Thatcher and Brown (2010) indicated that mediated communication has an indirect influence on creativity Research by McCoy and Evans (2002) highlighted the importance of a creative physical environment in fostering creativity, while Jan Dul et al (2011) found that a supportive physical work environment enhances workers' creative output In contrast, computer-mediated communication offers a modern and appealing interface that may also contribute to creativity Based on these findings, the following hypothesis is proposed.

H2a: Computer-mediated communication has a positive impact on engineers’ creativity in the semiconductor industry

According to AMO theory, communication is a key factor in enhancing individual performance, particularly within the context of Computer-Mediated Communication (CMC), which is crucial for the social environments where individuals work (Fulk et al., 1990) CMC facilitates virtual teams and enhances member engagement, making it an effective tool for boosting productivity and overall team performance (Ehsan et al., 2008) Since team performance is ultimately a reflection of individual contributions, this leads to the formulation of a relevant hypothesis.

H2b: Computer-mediated communication has a positive impact on engineers’ task performance in the semiconductor industry.

Employee agility and engineer performance

Employee agility is defined as the ability to think and act flexibly in response to rapid and unpredictable changes in the workplace It encompasses the capacity to anticipate new demands and challenges, enabling individuals to adapt quickly and proactively to evolving circumstances This adaptability is crucial for leveraging change as an opportunity for growth and involves qualities such as flexibility, openness to change, and a willingness to learn new skills.

Numerous studies have highlighted a significant connection between employee agility and creativity (Zhou & George, 2001) Research by Zhou & Shalley (2007) indicates a positive correlation between adaptability and creativity, suggesting that individuals who are more adaptable tend to demonstrate higher creative levels Additionally, those with proactive personalities are more inclined to engage in creative behaviors and generate innovative ideas In the fast-evolving technological landscape, it is crucial for engineers to remain agile in their adaptation to new tools and technologies, as agile employees are generally more receptive to learning and experimenting with emerging technologies (Muduli).

& Pandya, 2018), which can fuel their creativity They can explore novel approaches, leverage new tools, and experiment with cutting-edge solutions, resulting in more creative and innovative engineering outcomes

Research has highlighted the significant relationship between employee agility and task performance Miao, Q., Newman, and Schwarz (2019) found that employee adaptability, a crucial aspect of agility, positively influences task performance, indicating that more adaptable employees achieve higher performance levels Similarly, Shin and Hur (2019) examined the impact of employee agility on engineers' performance in agile development, revealing that individuals with greater agility tend to excel in their job roles Based on these findings, the following hypotheses are proposed.

H3a: Employee agility has a positive impact on engineers' creativity

H3b: Employee agility has a positive impact on engineers' task performance h

Employee agility moderates the relationship between communication

In the Agile development framework, team members are encouraged to prioritize face-to-face interactions, as this approach fosters enhanced creativity and collaboration (Fowler & Highsmith, 2001; Lindvall, 2002) Research indicates that agile employees tend to demonstrate improved job performance (Ployhart & Bliese, 2006; Ellis et al., 2003; Bondarouk & Ruởl, 2009; Yuen & Kee, 2017) Their adaptability enables them to effectively utilize various communication channels, whether in-person, virtual, or a combination of both (Breu et al., 2002) This agility allows them to leverage the strengths of different mediums, enhancing their ability to convey information, collaborate, and coordinate tasks, ultimately leading to superior task performance.

Agile employees excel at quickly adapting to new communication technologies and platforms, allowing them to effectively learn and utilize computer-mediated communication (CMC) tools This adaptability enhances their communication and collaboration skills, positively influencing the relationship between CMC usage and job performance By leveraging the full potential of these tools, agile employees can achieve improved outcomes in their work.

H4a: Employee agility moderate relationship between FTFC and engineers' creativity H4b: Employee agility moderate relationship between FTFC and engineers' task performance

H4c: Employee agility moderates the relationship between CMC and engineers’ creativity

H4d: Employee agility moderates the relationship between CMC and engineers’ task performance

Base one the hypotheses, a conceptual model is illustrated as figure 3.1 in the next page h

Table 3 1: Description of constructs and supporting literature

Face-to-face communication takes place in person, allowing individuals to interact directly and exchange information through their physical presence This mode of communication encompasses both verbal and nonverbal elements, including speech, facial expressions, body language, and eye contact.

Computer-mediated communication (CMC) is a communication medium to the exchange of information, ideas, or messages between individuals or groups using digital technologies or computer systems

Engineers’ creativity is an ability of engineers to generate ideas, solutions, concept, designs, and approaches to solve problems or innovate new features

Engineers task performance is specific activities and behaviors that engineers engage in to fulfill their job requirement and contribute to their field of expertise

Employee agility is ability to adapt, learn, and perform effectively in a rapidly changing work environment It charactered by Proactivity, adapability, resiliency

RESEARCH METHODOLOGY

Research design

This study investigates the impact of communication mediums on engineer performance within semiconductor companies utilizing agile development in new product processes By employing a quantitative approach, it aims to enhance our understanding of how communication mediums affect performance, particularly considering the moderating role of employee agility Data analysis was conducted using IBM SPSS Statistics Subscription Trial version 26 for reliability testing and exploratory factor analysis, alongside SmartPLS 4 trial version for SEM modeling and moderating effect analysis.

Measurements

The research utilized a questionnaire featuring multiple-item scales, adapted from previously validated measures The structural model includes five key constructs: FTFC, CMC, Engineers' Creativity, Engineers' Task Performance, and Employee Agility Measurement items for FTFC and CMC were developed based on the work of Thatcher & Brown (2010), employing a 7-point Likert scale ranging from 1 (never) to 7 (many times a day) for team member interactions, and from "A Few times a year" to "daily" for whole team meetings Engineers' Creativity was modified from Mittal and Dhar (2015), while Task Performance was derived from Williams and Anderson (1991), and Employee Agility was adapted from Thomas et al (2017), with a 7-point scale from 1 (Strongly disagree) to 7 (Strongly agree) Additionally, the research included two open-ended questions aimed at uncovering the actual communication mediums and engineers' opinions regarding their company's communication practices.

Questionnaire and Pilot testing

The survey starts with an introduction outlining its objectives, question types, and ethical considerations It is divided into four sections: Section 1 features screening questions to identify engineers and collect demographic data like age and education Sections 2, 3, and 4 contain multiple-choice questions focused on gathering responses related to specific constructs.

The research focused on semiconductor companies utilizing agile development, with respondents from both Vietnam and abroad To facilitate understanding, the questionnaire was created in both English and Vietnamese Prior to the official survey distribution, the questionnaire underwent a translation pretest, and qualitative interviews were conducted with respondents to ensure clarity and comprehensibility of the translation.

Data collection

The Data collection was implemented by two steps

Step 1: Collect information on the semiconductors company and interviews with the manager level to confirm the existence of agile development in each target company

Step 2: Distributing the survey on a large scale within confirmed companies that adopt agile development

Data was gathered using a survey instrument sent via email to confirmation companies, while a second survey targeted engineers in semiconductor firms employing agile development through direct outreach on LinkedIn.

The research utilizes Partial Least Squares-Structural Equation Modeling (PLS-SEM) to analyze the collected data As recommended by Barcelay et al (1995) and Henseler et al (2014), the minimum sample size for a PLS model should be at least ten times greater than the highest number of internal model paths directed towards any specific entity within the internal model.

To ensure sufficient statistical power and reliable results while reducing the risk of overfitting, a minimum sample size of thirty participants is recommended based on the theoretical framework Consequently, the anticipated sample size should exceed thirty individuals to meet this benchmark for effective analysis.

Data analysis

The data collected in this study are analyzed using SPSS and SMART PLS 4.0 SPSS is used to assess the reliability and validity of the variables, while PLS-SEM is applied to estimate and test the model's hypotheses The choice of PLS-SEM is driven by its significant advantages in structural equation modeling.

- It is capable of handling data with non-normal distribution

- It allows for estimating complex models involving numerous factors, latent and observed variables, and structural paths, even if sample sizes are small

- PLS-SEM is causal foreboding access to structural equation modeling that focuses on prediction within the process of estimating statistical model (Hair, Risher, Sarstedt, & Ringle, 2019)

As said by Hair et al (2019), the PLS-SEM model is assessed through the measurement model and the structural model

Out of 300 survey invitations sent, 117 responses were received, resulting in a response rate of 39%, which is lower than expected Despite this, the feedback gathered from the 117 participants provides valuable insights.

18 were excluded from the analysis due to incomplete answers Hence, the final sample size used for data analysis consists of 99 engineers

Table 4 1: Profile respondent by age

Category Frequency Percent Valid Percent Cumulative Percent

Category Frequency Percent Valid Percent Cumulative Percent

The table 4.2 present that, most of engineers in semiconductor industry aged from 27-

At 42 years old, individuals in the semiconductor industry demonstrate optimal work performance, with 68.7% of respondents indicating this age as advantageous Notably, 83.8% of participants hold a bachelor's degree, highlighting the educational qualifications prevalent in the field The survey also reveals that the semiconductor sector in Vietnam remains relatively young, suggesting significant growth potential for target companies operating within the country.

The reliability and validity of the variables were assessed using SPSS software, revealing a Cronbach's Alpha ranging from 0.869 to 0.881, indicating strong reliability Additionally, the KMO measure of sampling adequacy exceeded 0.71, with a significance index below 0.001, confirming statistical significance.

The results of the exploratory factor analysis (EFA) have been organized into five distinct groups (see Appendix 1), with several items removed to enhance statistical accuracy Notably, two factors containing only two items were retained due to their Cronbach's alpha exceeding 0.8, indicating high internal consistency (Yong & Pearce, 2013; Tabachnick & Fidell, 2007) Additionally, this research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) for analysis, ensuring that each group aligns with the definitions of their respective constructs.

Possible reasons for the formation of pattern matrix groups and the elimination of items include a small sample size, inadequate question design, and inaccurate ratings by respondents.

After conducting an Exploratory Factor Analysis, the model was further examined using SmartPLS 4.0 through Confirmatory Factor Analysis The measurement model assesses the unidirectional relationships of items that measure a single construct This evaluation involves analyzing the reliability, convergent validity, and discriminant validity of these items, as outlined by Hair et al.

To achieve a satisfactory level of item reliability, observed variables should have an outer loading value exceeding 0.708, which signifies that the construct explains over 50% of the variation in the indicator Furthermore, to confirm the internal consistency reliability of the scale, it is recommended that Cronbach's alpha values range from 0.7 to 0.95 These values reflect a desirable level of internal consistency, ensuring that the scale's items consistently measure the same underlying construct.

Convergent validity is a key criterion for evaluating scale validity, assessed through the average variance extracted (AVE) A satisfactory AVE value is 0.5 or higher, indicating that the construct accounts for 50% or more of the variance in its components, as established by Fornell and Larcker (1981).

Discriminant validity is crucial for ensuring that factors measuring different constructs do not have significant associations To evaluate this, the square root of the Average Variance Extracted (AVE) is compared to the correlations between constructs, as per Fornell and Larcker's (1981) guidelines Each construct's AVE should exceed its correlations with other constructs, indicating distinctiveness and minimal overlap However, Fornell-Larcker's method may be less effective when indicator loadings are only slightly different To overcome this limitation, the Heterotrait-Monotrait (HTMT) ratio is introduced, where a construct is deemed distinct if its HTMT value is below 0.85 This research utilizes both Fornell-Larcker and HTMT criteria to provide a more thorough assessment of discriminant validity, addressing potential shortcomings of relying solely on Fornell-Larcker.

After obtaining the outcomes of the measurement model, the structure of model is utilized to analyze the connections among construct The assessment criteria for this phase are as follows:

To assess collinearity in a structural model, it is essential to analyze the relationships among factors The variance inflation factor (VIF) serves as a key metric for detecting multicollinearity; VIF values above 5 suggest a significant risk of collinearity among predictor constructs Additionally, VIF values between 3 and 5 may also raise collinearity concerns For optimal results, VIF values should ideally be 3 or lower (Hair et al., 2019).

R-square, which assesses the extent to which an independent variable explains the variance in the dependent variable, serves as an indicator of themodel's appropriateness According to Henseler et al (2009), an R-square value of 0.67 is considered strong, indicating that the independent variable has a substantial explanatory power over the dependent variable A value of 0.33 is considered moderate, suggesting a moderate level of explanatory power, while a value of 0.19 is considered weak, implying a lower level of explanatory power in PLS models

The effect size f² is used to evaluate the impact of removing a predictive construct on the R² value of an endogenous construct Hair et al (2019) classify f² values as follows: 0.02 indicates a small effect, 0.15 a medium effect, and 0.35 a large effect, reflecting the relevance of variables in explaining dependent variables within a structural model These effect sizes offer valuable insights into the magnitude of effects and the importance of constructs in elucidating the dependent construct.

The path coefficient in the PLS structural model, derived from the standardized beta coefficient of regression least squares, effectively validates the theoretical relationships among latent variables Additionally, the non-parametric bootstrap method in PLS path modeling allows for the creation of confidence intervals for parameter estimates, enhancing the process of statistical inference.

The bootstrap sampling process involves randomly selecting cases from the original sample with replacements to create multiple bootstrap samples For each of these samples, Partial Least Squares (PLS) estimates the path model coefficients, generating a bootstrap distribution of these coefficients This distribution serves as an approximation of the sampling distribution, facilitating the calculation of mean values and standard errors for each path model coefficient derived from all bootstrap samples Consequently, this enables the assessment of the significance of the path model relationships using a student's t-test (Henseler et al., 2015).

A t-value exceeding 1.96 indicates statistical significance at the 5% level, providing evidence of the significance of the tested relationships h

DATA ANALYSIS AND RESULTS

Assessing PLS-SEM model

The model's assessment followed the guidelines established by Hair Jr., Sarstedt, Hopkins, and Kuppelwieser (2014) and Hair et al (2019), focusing on key factors such as reliability, convergent validity, and discriminant validity.

Table 5 1: Abbreviations of variable in the model

FC Face-to-face communication medium

Figure 5 1: The measurement model (PLS algorithm) h

The initial application of the Partial Least Squares (PLS) algorithm indicated that the observed variables had outer loadings exceeding 0.7 However, a detailed analysis revealed that one item from the EC category, three items from the TP category, and two additional items required further scrutiny.

Six items from the analysis were eliminated due to their outer loadings falling below the 0.7 threshold After this removal, the PLS algorithm was rerun, resulting in all remaining observed variables showing outer loadings greater than 0.7, as detailed in Table 5.2.

Table 5 2: Outer loading for algorithm

Item EA EC FC MC TP EA x FC EA x MC

The results presented in Table 5.3 demonstrate that all factors achieved reliable performance, with Cronbach's Alpha (CA) values ranging from 0.711 to 0.893, all exceeding the acceptable threshold of 0.7 Furthermore, the Average Variance Extracted (AVE) for each construct was above the minimum criterion of 0.5, with values between 0.716 and 0.822 (Hair et al., 2014) These results strongly support the convergent validity of the constructs, confirming their effectiveness in measuring the intended concepts.

The Fornell and Larcker Criterion reveals that the square roots of AVE values for each construct range from 0.846 to 0.894, exceeding the 0.5 threshold (Table 5.4) Furthermore, the square root of AVE for each construct is greater than the correlation coefficients with other constructs in the same column These results demonstrate satisfactory convergent and discriminant validity, confirming that the constructs are distinct and effectively measure unique aspects of the research variables.

Table 5 4: Discriminant validity according to Fornell- Larcker Criterion

EA EC FC MC TP

The analysis of HTMT (Heterotrait-Monotrait) values revealed that all constructs had values below the threshold of 0.85, confirming their discriminant validity This indicates that the constructs are distinct from one another, demonstrating greater similarity within their own constructs compared to others Consequently, the findings affirm that the constructs are adequately distinguishable and possess sufficient discriminant validity.

Table 5 5: Discriminant validity: Heterotrait - Monotrait Ratio (HTMT)

EA EC FTFC MC TP EA x FTFC EA x MC

Table 5.4 presents the correlation matrix, illustrating the relationships among various constructs The analysis identifies both positive and negative correlations, highlighting a significant positive correlation of 0.494 between EC and EA Additionally, a positive correlation of 0.1914 is noted between FC and EC, while MC also shows a positive correlation of 0.046 with EC Furthermore, a positive correlation of 0.192 exists between MC and TP, alongside a positive correlation of 0.086 between FC and other variables.

The study reveals notable negative correlations among certain variables, as shown in Table 5.5 Specifically, a negative correlation of -0.163 exists between TP and EAxMC, indicating an inverse relationship Additionally, a negative correlation of -0.064 is found between EC and EAxMC, suggesting a similar inverse association These results emphasize the coexistence of both positive and negative relationships among the variables examined in the research.

The observed correlations among the variables indicate the presence of linear relationships, aligning with Taylor's (1990) findings Additionally, structural model analysis further validated these correlations, offering deeper insights and explanations for the data.

Table 5 6: Correlation of latent variable

EA EC FTFC MC TP EA x FC EA x MC

Analysis the structure of model

Following the assessment of the measurement model's reliability and validity, the structural model was evaluated using the Bootstrapping technique with 5,000 resamples This method allows for robust estimates of model parameters and tests their significance Through this approach, the relationships and hypotheses outlined in the structural model were rigorously analyzed, ensuring a comprehensive evaluation of the model's overall fit and statistical significance.

Figure 5 2: Structural model (PLS Bootstrapping two tails) Multicollinearity

Before testing the formulated hypotheses, it is essential to assess multicollinearity The calculation of Variance Inflation Factor (VIF) values indicates that the relationship among the predictors does not breach the multicollinearity assumption, as all coefficients fall within the acceptable range (VIF values range from 1 to 1.891, which is below the threshold of 3).

Table 5 7: Collinearity statistics (VIF) of exogenous variables

EA EC FTFC MC TP EA x FTFC EA x MC

To effectively evaluate the inner path model estimates, it is crucial to depend on reliable outer model estimations The primary criterion for this assessment is the coefficient of determination (R2) for the endogenous latent variables, as highlighted by Henseler et al (2009) This metric measures how well the model explains the variation in the endogenous construct, enabling researchers to evaluate its effectiveness in predicting and understanding relationships between latent variables The analysis reveals that the R2 value for the engineer creativity model is 0.297, while the engineers task performance model has an R2 value of 0.252 (see Table 5.8) These results indicate that the R2 in the PLS path models is at a moderate level (Henseler et al., 2009).

The effect size of an exogenous construct on an endogenous construct is represented by f², as outlined by Hair et al (2019) An f² value of 0.02 indicates a small effect, 0.15 signifies a medium effect, and values above 0.35 reflect a large effect This metric provides valuable insights into the strength and practical significance of the relationship between independent and dependent variables in a regression model According to Table 5.9, most predictor constructs exhibit small to medium effects on the endogenous variables Consequently, the removal of an exogenous construct would result in a weak to moderate influence on the R² value, highlighting its small to medium effect size on the endogenous construct.

Table 5 9: F square f-square Effect level

The proposed hypotheses are tested by the estimation of coefficients and p-value (Table 5.10) The empirical evidence only supported 03 hypotheses, as seen in table 15 The other hypotheses are not supported

The study confirms that employee agility significantly enhances engineers' creativity (β = 0.478, p < 0.01) and positively influences their task performance (β = 0.420, p < 0.01) These findings indicate that employee agility plays a crucial role in improving engineers' overall performance within the semiconductor industry.

The study examines the relationship between communication mediums and engineer performance, revealing that hypotheses H1a, H1b, H2a, and H2b are unsupported This indicates that both face-to-face communication and computer-mediated communication do not have a direct impact on engineers' performance in terms of creativity and task execution Additionally, hypotheses H4a and H4b were also considered in the analysis.

H4c, and H4d predict that employee agility will moderate the relationship of communication medium and engineers' performance

The findings indicate that only the H4c hypothesis is supported, with a coefficient of β = -0.283 and a p-value less than 0.05, signifying a moderate relationship between employee agility, computer-mediated communication, and engineer creativity In contrast, hypotheses H4a, H4b, and H4d were not supported, as their p-values exceeded 0.05.

Table 5 10: Results of the hypothesis testing from the structural model

FTFC -> EC 0.113 0.820 0.412 H1a is not supported

FTFC -> TP 0.005 0.043 0.966 H1b is not supported

MC -> EC -0.026 0.189 0.850 H2a is not supported

MC -> TP 0.200 1.597 0.110 H2b is not suppported

EA x FTFC -> EC 0.145 1.389 0.165 H4a is not supported

EA x FTFC -> TP -0.054 0.395 0.693 H4b is not supported

EA x MC -> EC -0.283 2.278 0.023 H4c is supported

EA x MC -> TP -0.166 1.163 0.245 H4d is not supported

Sourced: PLS boostrapting two tail h

Figure 5 3: Path diagram base on analysis result

Figure 5 4: Simple slope analysis (Source: Pls bootstrapping two tail) h

DISCUSSION AND CONCLUSION

Discussion

6.1.1 Communication Medium and Engineers’ Performance

Recent findings indicate that communication mediums, specifically face-to-face communication (FTFC) and computer-mediated communication (CMC), do not directly influence engineer performance in agile development This lack of impact contradicts the fundamental objectives of agile methodology as outlined by Beck et al (2001) Additionally, the relationship between CMC and engineer performance challenges the assumptions of the Ability-Motivation-Opportunity (AMO) theory proposed by Cummings and Schwab.

1973) It is possible to have an indirect relationship between the Communication medium and the engineer’s performance through different approaches

Research conducted in the semiconductor industry within an agile development framework indicates that face-to-face communication does not significantly enhance engineers' task performance or creativity This challenges the prevailing belief that such communication is crucial for success in agile environments, as previously suggested by Turk & Rumpe (2002), Beck et al (2001), and Stettina & Heijstek (2011).

6.1.2 Employee agility and Engineers’ Performance

The finding proves there is a positive impact of employee agility and engineer performance That presents results that aligns with AMO theory (Jeffrey & John, 1999) and Amabile’s theory of creativity component

Research highlights the significance of employee agility in cultivating engineers' creativity within agile development environments Agile teams with more agile employees tend to exhibit higher levels of creativity, aligning with previous studies that emphasize the positive impact of individual attributes, such as openness to experience and learning orientation, on creative performance.

The analysis revealed a significant positive correlation between employee agility and engineers' task performance (r = 0.420, p < 0.001), highlighting the importance of agility in enhancing performance within agile development teams Agile teams with highly agile employees tend to demonstrate superior task performance, aligning with the AMO theory, which posits that employee agility enhances both the ability and motivation components of the framework.

The findings may not be universally applicable to other countries or industries due to several key factors Firstly, the companies in focus primarily operate in a globalized environment, embracing national and multicultural diversity, which results in a varied workforce comprising individuals from different backgrounds Secondly, the semiconductor industry exhibits a significant gender imbalance, with a predominance of male employees (Achyldurdyyeva et al., 2019) This sector is also characterized by rapid advancements driven by Moore's law, further complicating the dynamics of diversity within the workforce.

6.1.3 Roles of employee agility on the relationship between a communication medium and engineers’ performance

Research findings indicate that employee agility significantly influences the relationship between computer-mediated communication (CMC) and engineers' creativity Specifically, highly agile engineers experience a negative impact from CMC on their creativity, while those with lower agility benefit positively from it This suggests that CMC often lacks the richness of non-verbal cues and immediate feedback found in face-to-face interactions, which can hinder swift information processing and contextual understanding essential for creativity Consequently, CMC may stifle spontaneous idea generation and creative brainstorming due to its asynchronous nature, which disrupts the natural flow of ideas and limits rapid iteration.

Similar to part 6.1.2, this finding can be applied in other countries but not in other industries.

Practical implication

Research highlights the need for semiconductor industry managers to foster employee creativity and task performance to boost productivity during agile development in R&D Striking a balance between computer-mediated communication (CMC) and face-to-face interactions is essential, especially for tasks demanding high creativity and spontaneous idea generation In-person communication offers a depth of interaction that CMC often lacks, enhancing agility and promoting innovative thinking.

Organizations aiming to promote a creative work environment in agile development teams should consider fostering employee agility through targeted training programs, supportive leadership, and a culture that encourages experimentation and learning

Managers should focus on boosting the employee agility of engineers to improve engineers' creativity by training, and proactively use face to face communication at work

The CMC’s makers are recommended to improve the creative and attractive interface that could increase the creativity of users.

Theoretical implication

Research findings support Media Richness Theory, demonstrating that face-to-face communication is a more effective medium than computer-mediated communication The richness of face-to-face interactions is attributed to the depth of non-verbal cues, immediate feedback, and tone, all of which enhance information richness.

Employee agility significantly enhances engineers' creativity, aligning with Amabile's assertion that individual traits and attitudes are crucial for fostering creative output Furthermore, Amabile's theory emphasizes the importance of the work environment in nurturing creativity In agile development settings, which prioritize flexibility, collaboration, and experimentation, the role of employee agility becomes increasingly vital in cultivating a creative atmosphere.

The findings align with AMO theory (Jeffrey & John, 1999), highlighting that employee agility is a key component of ability Employees exhibiting higher levels of agility tend to be more motivated to learn and enhance their performance This relationship suggests that organizations offer opportunities for employees to effectively utilize their agility, ultimately demonstrating a significant positive correlation between employee agility and engineers' task performance, thus reinforcing the principles of AMO theory.

Limitations and future research recommendations

This study faces several limitations that future research could address The primary limitation is the small sample size, with only 117 respondents and 99 valid samples from engineers in semiconductor companies utilizing agile development in their R&D processes This lower-than-expected sample size may hinder the generalizability of the findings Additionally, most participants were engineers from fabless models in Vietnam, which could restrict the external validity of the results Future studies should focus on larger sample sizes and a broader geographic scope to improve the representativeness of the findings.

The questionnaire survey included open-ended questions to gather information on various communication mediums, but it did not specifically address mobile-mediated communication Considering the rising use of mobile devices and secure communication apps in the R&D process, future research should focus on the influence of mobile-mediated communication on engineer performance in agile development This exploration would enhance our understanding of the communication methods utilized by engineers in the semiconductor industry.

The author primarily emphasizes communication mediums, neglecting critical elements such as communication quality and modes, including verbal, non-verbal, and written forms Future research should delve into these specific aspects of communication to uncover the hidden connections between communication practices and engineers' performance.

Future research should investigate the impact of employee agility on creativity, considering contextual factors that may influence this relationship A deeper understanding of how employee agility affects engineers' creativity can help organizations enhance their agile practices, fostering an environment that maximizes the creative potential of development teams Additionally, examining factors like team dynamics, leadership styles, and organizational culture could yield valuable insights into the connections between employee agility, creativity, and overall team performance.

Conclusion

The findings indicate that the practical investigation successfully met its objectives and addressed the research questions This paper sought to create a conceptual framework for assessing the impact of communication on engineers' performance within an agile development setting Utilizing the PLS-SEM method, the study analyzed and validated the proposed hypotheses, leading to significant outcomes.

Face-to-face communication significantly enhances engineers' creativity in agile development within the semiconductor industry compared to computer-mediated communication This insight aids managers in selecting and balancing communication methods effectively within their organizations Additionally, fostering employee agility is crucial for boosting engineers' performance and overall productivity.

The research findings support established theories, highlighting that face-to-face communication, as per media richness theory, enhances creativity through rich non-verbal cues and immediate feedback Amabile's Theory of Creativity emphasizes the importance of individual factors and the work environment in fostering creative performance, underscoring the role of employee attributes within an agile development context Furthermore, Jeffrey Pfeffer's AMO theory illustrates how employee agility, as part of ability, plays a crucial role in enhancing both individual performance and motivation.

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APPENDIX 1: PATTERN MATRIX FOR EFA

Extraction Method: Principal Axis Factoring

Rotation Method: Promax with Kaiser Normalization a a Rotation converged in 6 iterations h

SUBJECT COMPANIES PROFILE

Business type Direct foreign investment

SURVEY QUESTIONNAIRES IN BILINGUAL

Section 1: GIỚI THIỆU VÀ CAM KẾT BẢO MẬT/ INTRODUCTION AND SECURITY COMMITMENT

A recent survey investigates the impact of effective communication channels on the performance of engineers involved in product development The study highlights how the choice of communication medium significantly influences collaboration, productivity, and innovation among engineering teams By examining various communication methods, the research emphasizes the importance of clear and efficient information exchange in enhancing engineers' work efficiency and overall project success The findings suggest that optimizing communication strategies can lead to improved outcomes in product development processes.

Mình là Lưu Thị Ngân, hiện là học viên cao học chương trình Thạc sĩ Quản trị kinh doanh của Trường Đại học Việt Nhật

Tôi đang tiến hành một nghiên cứu nhằm nâng cao hiệu quả làm việc của kỹ sư dưới sự hướng dẫn của GS.TS Kurata Hisashi từ Đại học Quốc lập Yokohama, Nhật Bản, và Tiến sĩ Trần Huy Phương từ Đại học Kinh tế quốc dân, Việt Nam Tôi rất mong nhận được sự hỗ trợ từ bạn để hoàn thành bài nghiên cứu này.

Bảng câu hỏi sẽ gồm 31 câu, dự kiến cần 5-10 phút để trả lời Rất mong bạn bớt chút thời gian trả lời bảng hỏi

Dữ liệu thu thập sẽ được bảo mật và chỉ được sử dụng cho mục đích nghiên cứu khoa học sau khi phân tích thống kê, không phục vụ cho bất kỳ mục đích thương mại nào.

Xin chân thành cảm ơn bạn đã giành thời gian giúp mình hoàn thành đề tài nghiên cứu!

Mình luôn sẵn lòng chia sẻ kết quả nghiên cứu, bạn có bất kỳ câu hỏi gì vui lòng liên hệ mình theo thông tin dưới đây

Email: 21117018@st.vju.ac.vn / Helenluu2@gmail.com

My name is Luu Thi Ngan, and I am a student in the Master of Business Administration program at Vietnam Japan University

Currently, I am doing research related to engineers performance under the co-supervisor of Prof

Dr Kurata Hisashi (Yokohama National University, Japan) and Dr Tran Huy Phuong (National Economics University, Vietnam) Therefore, I hope to receive support from you to complete my research

The questionnaire includes 31 questions, expected to take about 5-10 minutes to answer Please take the time to answer the questionnaire

The information collected will be kept confidential, and the results of this survey are for scientific research purposes only after statistical analysis, not for any commercial purposes h

I sincerely thank you for your assistance in completing this survey!

I always expect to share research results If you have any concerns, do not hesitate to contact me at any time

Email: 21117018@st.vju.ac.vn / helenluu2@gmail.com

Section 2 of 5: PHẦN THÔNG TIN CHUNG/ GENERAL INFORMATION

1 DM1: Vui lòng cho biết độ tuổi của anh/chị / What is your age range?

Please indicate your highest level of education from the following options: a Associate Degree, b Bachelor Degree, c Master Degree, or d Doctorate.

3 SC1: Anh/chị có phải là kỹ sư? / Are you an engineer?

Section 3 of 5: CÂU HỎI KHẢO SÁT LOẠI I/ SURVEY QUESTION TYPE 1

Bạn vui lòng đánh giá tần suất trải qua những sự việc ở các mệnh đề dưới đây, theo thang đo từ

1 đến 7/ Please rate how often do you experience each of the following, on a scale of 1 to 7

2 Vài tháng 1 lần/ Every couple months

5 Vài lần một tuần/ A few times a week

7 Nhiều lần một ngày/ Many time a day

Please indicate how often you engage in face-to-face communication regarding work-related issues with your team members, using the provided scale.

Please indicate how often you engage in face-to-face discussions regarding work-related matters with your team leader, using the provided scale.

Please indicate how often you engage in face-to-face discussions regarding work-related matters with members of other teams, using the provided scale.

MC1 Q8 Vui lòng cho biết tần suất anh/chị trao đổi các vấn đề về công việc với thành viên trong nhóm của mình gián tiếp qua các kênh

(Email, thư thoại, video, khác (vui lòng nói rõ ở câu

In a professional setting, it's essential to assess how often team members engage with their leaders regarding work-related matters through non-face-to-face communication methods such as email, voicemail, and other specified channels Understanding this frequency can enhance team dynamics and improve overall communication effectiveness.

Kênh giao tiếp gián tiếp mà tôi sử dụng để trao đổi công việc với các thành viên trong nhóm là email và các ứng dụng nhắn tin trực tuyến Những công cụ này giúp tôi dễ dàng chia sẻ thông tin, tài liệu và ý kiến mà không cần gặp mặt trực tiếp Việc này không chỉ tiết kiệm thời gian mà còn tạo điều kiện thuận lợi cho việc phối hợp công việc hiệu quả hơn.

Please indicate how often you engage in non-face-to-face communication regarding work matters with your team leader, utilizing channels such as email, voicemail, or other specified methods in question Q9.1.

In the context of workplace communication, please specify the indirect communication channels you utilize to discuss work-related matters with your team leader, excluding face-to-face interactions Options may include methods such as email, voicemail, or other forms of communication, as indicated in Question Q9.

MC3 Q10 Vui lòng cho biết tần suất anh/chị trao đổi các vấn đề về công việc với thành viên nhóm khác gián tiếp qua các kênh

Please specify the frequency of your communication regarding work issues with cross-functional team members through non-face-to-face interactions, such as email, voice mail, or other methods.

Please specify the non-face-to-face communication channel you use to interact with other team members, such as email, voicemail, or any other method, as indicated in Question Q10.

Section 4 of 5: CÂU HỎI KHẢO SÁT LOẠI 2/ SURVEY QUESTION TYPE 2

Bạn vui lòng đánh giá tần suất trải qua những sự việc ở các mệnh đề dưới đây, theo thang đo từ

1 đến 7/ Please rate how often do you experience each of the following, on a scale of 1 to 7

1 Từ 0 tới vài lần một năm/ From Zero to A Few time a year

2 Vài tháng một lần/ Every couple of months

4 Vài tuần một lần/ Every couple of Weeks

6 Vài lần một tuần/ A few time a week

Nhóm làm việc của bạn có thường xuyên tổ chức các buổi gặp mặt trực tiếp để các thành viên tương tác với nhau không? Hãy đánh dấu tần suất trao đổi công việc của toàn bộ thành viên trong nhóm bằng cách chọn số dưới đây.

Toàn bộ thành viên trong nhóm của bạn có thường xuyên tương tác với nhau qua các công cụ giao tiếp trực tuyến như email, thư thoại, và họp trực tuyến không? Vui lòng chỉ rõ tần suất và các công cụ khác (nếu có) trong câu hỏi Q11.1.