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LUẬN văn THẠC sĩ impact of customer co creation behaviors on crowd local delivery service quality master’s thesis, vietnam national university, hanoi

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  • CHAPTER 1. INTRODUCTION (11)
    • 1.1. Necessity of the thesis (11)
    • 1.2. Research objectives (11)
    • 1.3. Research questions (11)
    • 1.4. Research scope (12)
    • 1.5. Structure of the research (12)
  • CHAPTER 2. LITERATURE REVIEW (13)
    • 2.1. Overview of value co-creation (13)
    • 2.2 Dimensions of customer co-creation behavior (19)
    • 2.3. Crowd logistics and crowd local delivery service (28)
    • 2.4. Logistics service quality (32)
    • 2.5. Research gap (35)
  • CHAPTER 3. RESEARCH MODEL AND METHODOLOGY ............................. 27 3.1. Dimensions of customer value co-creation behavior in crowd local food (37)
    • 3.1.1. Service delivery process of crowd local food delivery (37)
    • 3.1.2. Analyzing dimensions of customer co-creation behavior (39)
    • 3.2. Conceptual model and hypotheses development (40)
      • 3.2.1. Responsible behavior and quality of crowd local food delivery service 31 3.2.2. Feedback and quality of crowd local food delivery service (41)
      • 3.2.3. Advocacy and quality of crowd local food delivery service (42)
      • 3.2.4. Tolerance and quality of crowd local food delivery service (42)
    • 3.3. Measure items development (42)
    • 3.4. Research method (45)
  • CHAPTER 4. DATA ANALYSIS AND FINDINGS (46)
    • 4.1. Data collection and demographic results (46)
    • 4.2. Reliability test (48)
      • 4.2.1. Reliability analysis of Responsible behavior (48)
      • 4.2.2. Reliability analysis of Feedback (49)
      • 4.2.3. Reliability analysis of Tolerance (50)
      • 4.2.4. Reliability analysis of Advocacy (51)
      • 4.2.5. Reliability analysis of Quality (52)
    • 4.3. Factor analysis (53)
    • 4.4. Correlation test (55)
    • 4.5. Regression (56)
    • 4.6. Findings and implications (57)
  • CHAPTER 5. CONCLUSION (59)
    • 5.1. Contributions (59)
      • 5.1.1. Academic contribution (59)
      • 5.1.2. Practical contribution (59)
    • 5.2. Limitations (59)
    • 5.3. Future research (60)
  • Appendix 1. Survey form in both Vietnamese and English (68)
  • Appendix 2. Question items on customer co-creation behavior (Yi & Gong, 2013) (72)
  • Appendix 3. Question items on service quality (Stank et al., 2003) (73)

Nội dung

INTRODUCTION

Necessity of the thesis

Value co-creation is a key concept in modern marketing theory (Saarijọrvi, Kannan, & Kuusela, 2013) It has been approached from different perspectives and levels However, most of studies focus on the macro or meso level and leave the micro-level many unanswered questions Recently, crowd initiatives have risen in many business industries, especially logistics and believe to provide new means of logistics value co-creation (Carbone, Rouquet, & Roussat, 2017) The major type of crowd logistics – crowd local delivery gets more attentions from business internationally but very few from academic research It also fosters new need of measuring new service quality in its model All of these issues bring up an idea of investigate relation between customer co-creation behavior within crowd local delivery service and their perception of value

Service quality is always a vital concern for service business, especially the new type as crowd local delivery Since it relies much more on co-creation among involved actors in its nature of service model, it is important to understand potential relationship between service quality of crowd local delivery and customer co-creation behavior Based on insights from this potential relationship, effective implications that could improve service quality from customer co-creation could be suggested for practical businesses.

Research objectives

This research aims at measure the relationship between level of customer value co-creation behavior and service quality of crowd local delivery.

Research questions

“Which dimensions of customer co-creation behavior have impact on factors of crowd local delivery service?”

Research scope

Because of limitations in terms of survey scale, only type of food delivery is researched.

Structure of the research

This thesis consists of 5 chapters:

 Chapter 1: Introduction – revealing basic ideas of the research in terms of background, objectives, subject and scope of the research

 Chapter 2: Literature review – building comprehensive understanding over very complicated concept of value co-creation as well as background to promote refined logistics service quality measurement for the new crowd business initiatives in logistics industry

 Chapter 3: Research model and methodology – describing the conceptual model and how the research is designed and carried out

 Chapter 4: Data analysis and findings – discussion of research results

 Chapter 5: Conclusion – summarizing the contributions, limitations and intentions for future research

LITERATURE REVIEW

Overview of value co-creation

Research stream of value co-creation rooted in the observation of changing roles between customers and firms Customers have been long considered as passive actor in value creation Traditionally, under the assumptions and models of industrial economy (R F Lusch & Vargo, 2014a, 2014b); Porter (2008); (Stephen L Vargo &

Lusch, 2008; Stephen L Vargo & Lusch, 2011) value is only created for customers and its creation is driven by value-adding activities (Normann & Ramirez, 1993)

Both of technological advances and changes of management towards unconventional and innovative ways of integrating resources for the creation of value lead to new forms and shapes of interaction that replace this traditional dyadic relationships

Value creation should not be limited in the manufacturing process, but extends over consumption contexts under customers’ own control (Grửnroos, 2008a; R F Lusch

& Vargo, 2014b) The focus is shifting from value creation to co-creation in order to realize the new role of customers It is crucial for firms to comprehend the logic of business ecosystems facilitating value co-creation, in order to gain and maintain competitiveness As a result, value co-creation is one the most important concept within service marketing and business management (Saarijọrvi et al., 2013)

Currently, there are multiple ways to approach value co-creation Each approaches target value co-creation from different perspectives, scopes and level of abstraction, thus they provides a complex of definitions, dimensions and interactions among actors (Galvagno & Dalli, 2014) It is both of practical examples such as Dell, Lego… and academic arguments that contribute to the fragmentations and diversification (Di Gangi & Wasko, 2009; Hienerth, Keinz, & Lettl, 2011) The major approaches to value co-creation are discussed in the following parts

Instead of dyadic relation between firms and customers, this approach promotes the role of customer networks and the importance of other factors from broader view, such as employees, marketing intermediaries, and society during the co-creation process of value (Gummesson, 2007) Edvardsson, Tronvoll, and Gruber (2011) have presented a social constructionist approach that only considers value co-creation in the social context and uses the holistic concept of value as “value-in-social-context”

New product and service development

Customers tend to be more active and willing to involve in the firms’ new product/service development process The involvement of customers in the development process helps firms to discover the hidden needs of customers as well as take advantage of their creative potentials Nambisan and Nambisan (2008) have suggested that customer could have multiple roles in the development process, consist of product conceptualizer, designer, tester, support specialist and marketer This involvement of customer rises partly upon the facilitation of technological advances, especially the Internet (S Ohern & Rindfleisch, 2010)

Similar to new product and service development literature, the postmodern marketing also acknowledges the more active customers “who takes elements of market offerings and crafts a customized consumption experience out of these” (Fuat Firat, Dholakia, & Venkatesh, 1995) Customers require a more active role in production and in order to meet this demand and enable active participation of customers, marketers have to make their business processes more open (Bendapudi

& Leone, 2003; Firat & Venkatesh, 1995) This phenomenon is often referred as

“prosumption” that involves both production and consumption (Ritzer & Jurgenson,

2010) According to Bendapudi and Leone (2003), customers have attained a new role that traditionally attaches to the producers Thus, customers’ consumption is gradually viewed as a production process and requires “development of special skills” customer’s value creation also embraces not just the good or the service but additional resources (e.g information and knowledge) (Grửnroos, 2008b; R F Lusch & Vargo, 2014a) According to Fuat Firat et al (1995), the product does not consider as a

“finished” object but a process that “customer could immerse oneself and contribute inputs”

In the past decade, the stream of research on SDL has caught a lot of attentions of researchers for both the academic purposes and practical implications (Tommasetti, Troisi, & Vesci, 2017) Research on SDL (R F Lusch & Vargo, 2014a, 2014b;

Stephen L Vargo & Lusch, 2008; Stephen L Vargo & Lusch, 2011) has intensified discussion about value co-creation because value co-creation is a key concept in SDL (Stephen L Vargo & Lusch, 2008) Despite that SDL is dominant theory in marketing and value co-creation, it is still a pre-theoretical paradigm (Cantone, Testa, &

Marrone, 2019) Stephen L Vargo and Lusch (2016) recognized the limitation of the current foundational premises/axioms of SDL that lacks explicit articulated specification of the co-creation mechanism Therefore, SDL to date could be regarded as a logic or mindset that includes many fragmentations of marketing (Gummesson,

2008) According to SDL, the logic of goods-centric thinking that marketing has inherited is less germane in the current service era This way of thinking has influenced how value and value creation are perceived In the new era with increasing relevance of service, service rather than goods, should be the fundamental unit of exchange, and goods only function as transmitters of services and means for customers to get benefits from firm competences (R F Lusch & Vargo, 2014a;

Stephen L Vargo & Lusch, 2008) Actualization of value of goods only happens if customers continue the value creation process “For these services to be delivered, the consumer still must learn to use, maintain, repair, and adapt the appliance to his or her unique needs, usage situations and behaviors” (R F Lusch & Vargo, 2014a)

Consumers are considers as source of operant resources that play essential role within resources integration during value creation Because operant resources are different and heterogeneous in each individuals, the capability of consumer skills and knowledge influences how value is created (Saarijọrvi et al., 2013) Thus value is a joint function of actions of consumers and producers (Ramaswamy & Prahalad, 2004), and is certainly always co-created (Stephen L Vargo & Lusch, 2008)

According to Stephen L Vargo and Lusch (2008), value co-creation consists of two components The first is the co-creation of value In SDL, at the intersection of the offer and the consumer, value is created and determined by the consumer in the consumption process The second component of value co-creation is co-production that refers to the involvement in the creation of the core offering itself Co-production can occur via shared ideas, co-design, or even shared production, with any partners in the value network

Dimensions of customer co-creation behavior

As the above discussion on different research approaches to value co-creation that varies in terms of perspectives, level of abstraction and scope The concept of value co-creation is studied from the either micro, meso or macro level of interaction level Among these different levels, to date, most of studies are on meso (R F Lusch,

2011) or macro (R Lusch & E Webster, 2011; Maglio & Spohrer, 2008; Wieland, Polese, Vargo, & Lusch, 2014) perspectives Thus, there are few answers about how interactions happen between customer and firm employee at the micro level (Neghina, Caniởls, Bloemer, & van Birgelen, 2015) Understanding this basic level of interactions is essential for better knowing the concept of value co-creation in larger contexts According to R F Lusch (2006) development of a detailed macro- marketing perspective is based on insights of micro-level Further discussions in this part are the most relevant studies of value co-creation at the basic level of direct interactions between customer and employee

Randall, Gravier, and Prybutok (2011) introduce a model of three variables to measure scale and analyze not directly value co-creation but only the relational feature of the concept Based on the adoption of mixed method and quantitative analysis, the authors suggest connection, trust and commitment as dimensions of value co-creation with question mark The study doubtfully departs from SDL and featuring customer relationship management approach (Tommasetti et al., 2017)

Gustafsson, Kristensson, and Witell (2012) focus on the role of communication in fostering co-creation and innovation The study identifies four categories of communication, including frequency, direction, modality and content

Communication however, is just a section in the interactions between firm and customer Therefore, main limitation of the study is its specific narrow scope of co- creation Moreover, the study approach is somewhat on the single corporate point of view

Third-order factor model of customer co-creation behavior

Yi and Gong (2013) introduce a third-order model that consists two major dimensions: customer participation behaviors and customer citizenship behaviors It is popular among the empirical studies on customer co-creation (Ahn, Lee, Back, &

Schmitt, 2019; Hau, Tram Anh, & Thuy, 2017; Hussainy, 2017) in various service industries While authors define customer participation behavior as a role behavior that is required for value co-creation process, customer citizenship behavior is voluntary and additional The citizenship behavior could help to bring extraordinary value to the firm but it does not consider as requirements for value co-creation like the participation behavior In short, customer participation behavior is in-role and customer citizenship behavior is extra-role behavior Separate scales are adopted to measure each type of behavior based on the empirical evidence that in-role and extra- role behaviors have different patterns and antecedents as well as consequences (M

Groth, 2005; Yi, Nataraajan, & Gong, 2011) In this model, each construct consists of four different lower-order dimensions

Figure 2.3 Third-order factor model with CFA results

Dimensions of customer participation behavior

 Information seeking: customers put effort into clarifying the requirements of service and satisfaction of other cognitive needs Provision of this these information helps to reduce the customers’ uncertainty about service interaction and value co-creation with employees Hence, customers could understand and manage the co-creation environment as well as their role of value co-creator

 Information sharing: from the side of customers, some resources are very important to achieve successful value co-creation with firm, such as information Without essential information, firm’s employees could not perform their duties as they are capable of By sharing this information with employees, customers themselves could make sure that the delivered service meets their specific needs

 Responsible behavior: Customers also have certain duties and responsibilities to comply with in order to have successful service delivery

Customers recognize their responsibilities to be cooperative, follow the service rules, policies, and directions from employees In case of lack of cooperative behavior from customers, little value could be created

 Personal interaction: this dimension represents interpersonal relations between customers and employees Different aspects of these type of human interactions could be take into account such as courtesy, friendliness, respect… In the social setting of value co-creation environment, people tend to be more likely to engage in co-creation if they feel more pleasant, congenial and positive

Dimensions of customer citizenship behavior

 Feedback: It is essential for firm and employees to improve the service creation process in the long-term Firm could be greatly beneficial as receiving suggestions from customers for better service Even though, feedback is not requisite for successful service result

 Advocacy: the behavior of customers that recommend firm or employees to other people Obviously, advocacy is effective word-of-mouth advertisement and could contribute significantly to establish firm’s positive fame Although this kind of behavior could represent the evidence of loyalty, it is voluntary and not required to perform the service delivery

 Helping: Customers could help each other to realize their value creation environment and roles of value co-creator It could be considered as a sense of social responsibility among customers to help each other under similar difficulties

 Tolerance: to some extent, customers could tolerate a certain failure of service to meet their expectation Mistakes and risks could always happen and be inevitable This kind of empathy toward firm could come from the belief of long-term fruitfulness from customers’ perspective

Based on the previous studies (Gustafsson et al., 2012; Karpen, Bove, & Lukas, 2012; Randall et al., 2011; Yi & Gong, 2013), Neghina et al (2015) introduce a model of customer value co-creation behaviors with six dimensions of joint activities and three antecedents This study is in line with the approach of service logic rather than SDL (Tommasetti et al., 2017)

Figure 2.4 Antecedents and dimensions of value co-creation

Crowd logistics and crowd local delivery service

The rise of crowd practices roots from the idea that each individuals could integrate their personal resources to perform traditional business activities via information technology (IT) platforms (usually websites and/or mobile applications) (Carbone et al., 2017) The word “crowdsourcer” was originally conceptualized as continuous evolution of the concept, it increasingly overlaps with sharing economy

Crowdsourcing is very similar to “peer-to-peer for-profit” model among four categories of sharing economy (Juliet, 2014) While crowd logistics has caught a lot of attentions in the business world (Carbone et al., 2017), there are very few research papers on this topic The first definition of crowd logistics is from the work of Mehmann, Frehe, and Teuteberg (2015) These researchers define crowd logistics as

“the outsourcing of logistics services to a mass of actors, whereby the coordination is supported by a technical infrastructure” Later study of Carbone et al (2017) aims at investigating different crowd logistics initiatives and characteristics by adopting online case study method over 57 initiatives In this study, crowd logistics is conceptualized as “being done through collaborative platforms and mobile apps that connect individuals and firms to peers in order to make the best use of distributed, idle logistics resources and capabilities.” Individuals perform logistics service tasks on an ad-hoc basis of crowd logistics

In each crowd logistics initiatives, based on the support of IT platform (either websites or mobile applications) the relationship between individuals in the crowd is built up and they could perform logistics tasks What crowd logistics initiatives offers individuals to connect to the platforms maybe in economic or noneconomic forms (Carbone et al., 2017) The core idea of crowd logistics initiatives is to match logistics assets and capabilities with needs of logistics Eventually, they helps to increase utilization of assets

The IT platform work as a market mediation between logistics capability and logistics demand Based on effective algorithms, IT platform help to balance the distribution of work flow to among individuals at the supply sides For the demand side, it provides the most suitable individual service provider for each case With the features of comments and rating, customers could be actively contribute to value creation and protect their benefits Between supply and demand simultaneously, it adopt flexible mechanism such as dynamic pricing that maintain profitable balance

Table 2.1 Comparison between business logistics and crowd logistics

Carbone et al (2017) summarize differences between traditional business logistics and crowd logistics initiatives Apart from the mentioned characteristics of crowd logistics, major limitation is amateur logistics skills and lacks of professional assets to special tasks Most of crowd logistics initiatives only could offer basic logistics services such as transport or storage because individuals in the crowd who perform logistics tasks do not have professional training or certified skills and just use their own ordinary assets like personal bikes, automobiles Increasing requirements of skills and assets also prevent expansions of the crowd, thus make the platform less attractive Besides that, instead of set of standardized KPIs, the qualitative type of performance measurement is applied in crowd logistics

Considering crowd logistics as new form of logistics value co-creation, Carbone et al (2017) adopted method from Saarijọrvi et al (2013) to analyze The authors dismantle the co-creation model of crowd logistics into three constituent parts including “value”, “co” and “creation” Value from crowd logistics service is influenced by the attractiveness of logistics advantages and perceived risk in opposite directions About resources for co-creation processes, crowd logistics rely on the availability of idle physical resources and simplicity of logistics tasks The mechanism of value co-creation in crowd logistics depends on the support of IT platform in terms of operation and transaction

Figure 2.6 Dismantling value co-creation in crowd logistics

As results of analyzing 57 crowd logistics initiatives, Carbone et al (2017) conclude four types of crowd logistics services They are crowd storage, crowd local delivery, crowd freight shipping and crowd freight forwarding Each type is embedded with different value propositions as well as particular resources and mechanisms Among them, researchers believe that local delivery service has the most potential impact Detailed characteristics of these crowd logistics initiatives are described in Table 2.2

Crowd local delivery service includes service for delivering parcels and foods

These two sub-criteria are different regarding to service process In crowd food delivery service, customer orders food from the restaurants on the mobile applications then the crowd shipper will be assigned to go to the restaurants and bring the ordered food to the customer In crowd parcel delivery service, customer asks crowd shipper to arrive in the picking-up location to take the parcel to the required destination

Within this research, only the food delivery service is investigated Apart from the difference of service delivery process, two kinds of crowd local delivery service share the same characteristics that are suggested in the study of Carbone et al (2017)

Table 2.2 Characteristics of local delivery service

Types of items Food, parcels

Types of logistics connections Local short distance

Logistics risk for users Lack of trust in the crowd

Crowd physical resources Cars, vans bikes, public transport

Crowd logistics capabilities Pickup, driving, riding, delivering

Logistics operational support by the platform GPS scheduling software

Logistics transactional support by the platform Pricing system, checking drivers’ licenses

Logistics service quality

There are two main streams of researches towards logistics service quality: from physical distribution service and from marketing with service quality theory The former one is the traditional approach to logistics service Because of changes in the business environment, operations-based definitions of logistics service that originally root from physical distribution service have been broadened New value-added concept widened logistics service; however, it was still operations-based Therefore, components of logistics service according to this approach all focus on the service provider In order to measure perceived value from customers’ perspective, the service quality literature from marketing is adopted It is inevitable because customers’ perspective of service quality is determinants of service satisfaction

Rinehart, Cooper, and Wagenheim (1989) and Mentzer, Gomes, and Krapfel

(1989) share the same opinion that there are two elements in service delivery: marketing customer service and physical distribution service (PDS) According to these researchers, PDS consist of three components: availability, timeliness and concept The use of customer-based concepts of logistics service quality help to transform physical distribution research more compatible with marketing Bienstock, Mentzer, and Bird (1997) follow the similar methodology as SERVQUAL (Parasuraman, Zeithaml, & Berry, 1988) to develop scale to measure quality of PDS from customers’ perspective It is conceptualized as physical distribution service quality (PDSQ) that consists of three first-order dimensions: timeliness, availability and condition Further development from this kind of mixed approach, T Mentzer, Flint, and Hult (2001) introduce a model of nine dimensions of logistics service quality (LSQ) that incorporates three stages of service delivery and process-based characteristics of logistics The nine dimensions are personnel contact quality; order release quantities, information quality, ordering procedures, order accuracy, order condition, order quality, order discrepancy handling, and timeliness This model is later refined and tested by Rafiq and Jaafar (2007) with adding more measure items and adoption of 7-point Likert scale instead of 5 in the context of 3PL service in the

UK Thai (2013) continues to develop the model with the aspects of corporate responsibility and sustainability, as well as image of the firm All of these studies are based on the business-to-business context, such as 3PL service industry

Another major trend of applying service literature from marketing is to adopt service quality model that is developed for service setting in general, such as SERVQUAL (Parasuraman et al., 1988) It is very convenient for researcher since the generic scale for measuring service quality was built Application of SERVQUAL is already popular in various service industries before expansion to logistics

However, researchers also argue on limitations of this model Because of differences among service industries, scale from SERVQUAL need customized in advance to fit each one Originally, SERVQUAL is created upon research of service quality in four cases: bank, credit card company, repair and maintenance company, and long- distance telephone company In all of these cases, service is a kind of close interaction between customers and employees and of course, logistics industry does not have these characteristics of service Another critical argument about SERVQUAL is the basis of quality In SERVQUAL, service quality is the gap between customers’ expectation and the actual perception of service Cronin Jr and Taylor (1992) criticize it because customers might be very difficult to measure their expectations In order to overcome this supposed limitation, they introduce SERVPERF model that use traditional concept of quality as excellence of performance Hence, instead of measuring both expectation and perception of service, only perception of service is evaluated However, SERVPERF is only recognized as a transformation of SERVQUAL because it applies the same scale and dimensions In reality, both SERVQUAL and SERVPERF are the most popular service quality model in logistics industry (Gulc, 2017)

Table 2.3 Dimensions of SERVQUAL (Parasuraman et al., 1988)

Considering the unique characteristics of logistics service and the mentioned limitations of SERVQUAL/SERVPERF application, Stank, Goldsby, and Vickery

(1999) combine five dimensions of SERVQUAL into two: operational performance and relational performance “Performance” implies that they follow the approach of Cronin Jr and Taylor (1992) towards concept of quality Operational performance consists of reliability (similar to the same name dimensions of SERVQUAL) and

“related to the consistent quality aspect of operational performance and price”

Relational performance contains responsiveness, assurance, and empathy dimensions could be considered as relational factor Stank, Goldsby, Vickery, and Savitskie

(2003) adjust the model in 3PL industry They separate cost as the third dimensions from operational performance Arguing that the model is mainly based on B2B context, Rao, Goldsby, Griffis, and Iyengar (2011) suggest to remove relational dimension as it is less relevant in case of e-LSQ with context of B2C

Figure 2.7 Conceptual model of e-LSQ

In case of crowd logistics service quality, it is crucial to take all mentioned characteristics of this new type of logistics service as well as the context that could be referred as C2B2C with mediation role of IT platform The logistics service literature that is traditionally developed for B2B environment should be carefully examined and refined when applies to crowd local delivery service as one type of crowd logistics.

Research gap

There are limited researches on value co-creation at the micro-interaction level, especially the empirical ones The dimensions of customer co-creation behavior are not clearly explained and overlapped across various researches Even the most recognized studies such as Yi and Gong (2013) only validated the model among graduate and undergraduate student customers and tested with recalled experiences from various industries All the suggested dimensions of customer value co-creation behavior are very general and should be customized in order to apply in a specific service type There have been no available researches on customer co-creation behavior in crowd local delivery service yet

Furthermore, it is not clear what possible consequences of customer co-creation behavior are The research focus is on antecedents rather than consequences (Frasquet-Deltoro, Alarcón-del-Amo, & Lorenzo-Romero, 2019) In the case of new service type as crowd local delivery that relies on co-creation among different actors including customer, it is important to investigate possible consequences of these co- creation behaviors

Service quality is always a critical concern for businesses Regarding to logistics service quality, this subject is still a contemporary topic (Gulc, 2017) Crowd local delivery service is a new type of logistics service that takes advantage of available idle personal resources from the crowd and co-creation among involved actors Scale for crowd local delivery service quality is not available yet and should be developed specifically in order to meet its unique characteristics and service delivery process

The service quality of the crowd local delivery is also considered as a remarkable consequence of customer co-creation behavior Thus, it is possible to investigate the relation between customer co-creation behavior and service quality in crowd local delivery service.

RESEARCH MODEL AND METHODOLOGY 27 3.1 Dimensions of customer value co-creation behavior in crowd local food

Service delivery process of crowd local food delivery

As the value proposition of crowd local delivery is speed, the service process is very easy and convenient for customer to use and simple enough for amateur shipper from the crowd to follow Via mobile application interface, the IT platform connect all involved actors, including restaurants, customers and food shippers from the crowd In terms of customers, they just need to follow the flow of the mobile application to use the service The application guides users step-by-step on the mobile phone screen Of course, at first, users need to install the application from the store for their smart phone operation systems, such as Apple’s App Store or Google’s Play Store

The first step is to launch the application After opening it, the application will ask users to provide the food delivery location This second step is often completed automatically or semi-automatically with location support from the application

However, the location function is not always accurate and the accuracy depends on many factors, including the users’ smart phone, Internet connection… at the moment of application usage

Figure 3.1 Crowd local food delivery process

After providing the food delivery location, the users need to choose the restaurant, starting with suggestions of nearby ones from the application Users could use search and filter function to find their desired restaurants, as well as manage their favorites and previous order information Then, they could choose the meal to order from the restaurants Further selections are likely available for users, such as size, flavor… of each meal In case of additional requirements or instructions in terms of meals or delivery address, users could write a note to inform the shippers Before completing the food order, users could apply their eligible promo codes that are quite frequently available

Right after users’ completion of food ordering, the application starts finding shipper for the order Assigning the order to a shipper depends on many factors

Enter note or promo code

Wait and get ready for delivery the restaurant of the ordered meal The platform also requires shippers to achieve a minimum rating level from the previous users, and it is very important for the platform to balance the workload among shippers to keep them stay with the crowd

After a shipper take the food order, the platform instantly informs user about the shipper’s information and start updating the service progress via interface of mobile application Shipper and user could contact each other by phone number or integrated communication functions inside the application, such as instant message or voice call over Internet connection Eventually, the user could get the food when the shipper arrive at the delivery location.

Analyzing dimensions of customer co-creation behavior

From literature, the model of Yi & Gong (2013) is adopted to measure customer co-creation behavior in crowd local food delivery service since it is the most significant empirical study The third-order model of customer co-creation behavior (Yi & Gong, 2013) covers general dimensions that may not all fit to a certain service type In total, this model consists of eight first-order dimensions: information seeking, information sharing, responsible behavior, personal interaction, feedback, helping, advocacy, and tolerance It is critical to examine the relevance of these dimensions in the case of crowd local food delivery

The crowd local food delivery service (the parcel delivery as well) is very simple in terms of service delivery process Its simplicity is crucial for the business model because of limitation from service providing capacity and skills The role of

IT platform is continuously to keep the service flow simple for both supply and customer side with its supporting functions in terms of operation and finance (Carbone et al., 2017)

Because of the service easiness to use and straightforward service flow, customer might not find it difficult to learn to use or they could directly follow guidelines on the applications From this point, the dimensions of information seeking, helping are unlikely related

The simple service process also limited interactions between shippers and customers The possible interaction should be very short conversation at the place of delivery (or picking up location in case of parcel delivery) With large crowd of individual shippers, customer may always interact with new shipper each time

Therefore, dimension of personal interaction is also not relevant

The great support regarding to operational function and simplicity of the service nature leads to very thin differences between the need to share information of customer’s need and required role of customer in the service delivery process Since the information sharing could be considered as responsible behavior in terms of order information In the whole service delivery process, the in-role responsibility of user is to provide information of meal and delivery location, and to be available to receive order at the arrival of shipper

After reconsidering relevance of established dimensions, only four dimensions remain in this service model: responsible behavior (combining information sharing and responsible behavior); feedback; tolerance and advocacy.

Conceptual model and hypotheses development

Based on the above discussion, the research model consists of four independent variables from four dimensions of customer co-creation behavior and one dependent variable of quality of crowd food local delivery service Four hypotheses of the model:

 H1: Customer’s responsible behavior positively affects the crowd local food delivery service

 H2: Customer’s feedback positively affects the crowd local food delivery service

 H3: Customer’s tolerance positively affects the crowd local food delivery service

 H4: Customer’s advocacy positively affects the crowd local food

According to J Groth and Dye (1999), “perceptions and expectations service often are the result of interaction” rather than the service itself Service quality as attitude and is the gap between expectation and perception (Parasuraman et al., 1988)

Each dimensions of customer value co-creation could have impact on the expectation or perception

3.2.1 Responsible behavior and quality of crowd local food delivery service

In order to have successful service delivery, both shipper and customer need to fulfill their duties and responsibilities (Ennew & Binks, 1999) The accuracy of information that customers provide as well as their synchronization with shipper help to achieve better perception of the service Therefore, level of customers’ responsible behavior could affect positively the service quality

3.2.2 Feedback and quality of crowd local food delivery service

In the long-term, the information and suggestion from customers to the businesses and employees could help to improve service creation process (M Groth,

2005) It is actually important resource integration between customers and service

Crowd local delivery service quality

H4 provider In case of crowd local food delivery, customer could provide useful suggestion to improve the service and their rating of shippers is the crucial measurement that keep service quality from these shippers in check The customers’ rating is important for the platform maintain the service quality from the crowd As a result, customer’s feedback help to improve service quality in long-term

3.2.3 Advocacy and quality of crowd local food delivery service

Advocacy is important behavior from the customers that contribute considerably to the growth of the businesses and could be an indicator of customer loyalty (Groth et al., 2004) Specifically, in case of crowd business, the customer base size is the most important factor and advocacy directly affect this aspect Further growth and development of the crowd local food delivery service would lead to higher service quality Hence, advocacy has positive impact on the service quality

3.2.4 Tolerance and quality of crowd local food delivery service

Tolerance is the customers’ willingness to be patient when the service delivery does not meet their expectation of adequate service (Lengnick-Hall et al., 2000) In the crowd local food delivery service, it is likely to happen because the shipper is not professional employee and does not have competent capacity to deliver service

Customers’ tolerance is essential for the service to growth The level of customers’ tolerance lead to low required expectation of service, thus it could result in large gap between customers’ expectation and perception of service.

Measure items development

Based on suggested questions items from literature (Appendix 2: items from Yi and Gong (2013); Appendix 3: items from Stank et al (2003)), the author has developed customized items that fit the actual service context and processes as presented in table 3.1 and 3.2 in order to measure customer co-creation behavior and service quality

The dimension of responsible behavior in this research presents customers’ from RB1 to RB4 are taken from the items of information sharing dimension from original model of Yi & Gong (2013) with more details of crowd local food delivery

The employee is particularly crowd shipper and required information is about food order and delivery location Items RB5 to RB7 reflect the role of customer to be available at delivery location to receive the food order Customers also could co- create in terms of synchronization between them and shippers (Neghina et al., 2015)

Item RB8 represent the customers’ decision to continue or cancel the service order, however it also relates to ethical aspect of customer co-creation behavior It is similar to dimension of ethical joint actions in Neghina et al (2015)

Table 3.1 Questions of co-creation behavior

RB1 You provide accurate delivery address

RB2 You provide sufficient order information

RB3 You provide appropriate information for shipper to deliver to the right place

RB4 You answer all order-related questions

RB5 You manage to be available at the delivered location on time

RB6 You pay attention to the mobile phone in order to receive the shipper's call

RB7 Arriving at the receiving place on time is important to your

RB8 You do not cancel order when shipper is leaving for it

Feedback FB1 You inform issues during using service

FB2 Rating shipper is important to you

FB3 You do rating each time using service

FB4 You do rating to complement good service of shipper

Tolerance TO1 You are patient when shipper is late

TO2 If shipper goes to wrong place, you wait for rerouting

TO3 You are willing to forgive shipper's mistakes

TO4 You suppose that shipper's mistake is ordinary

Advocacy AD1 You review positively about the service to others

AD2 You recommend this service to others

AD3 You encourage others using this service

AD4 You invite others to share order

The dimension of feedback in this research re-uses three original items from the same dimension of Yi & Gong (2013)’s model The only additional item is FB3 “You do rating each time using service” because instead of quantitative KPIs, the performance measurement of this crowd logistics service is in the form of convenient qualitative rating with stars and likes (Carbone et al., 2017) User could quickly give their rating over the shipper’s service

From the items of tolerance dimension of Yi & Gong (2013)’s model, the measure items for the same name dimension in this research consider the tolerance for the shipper’s late delivery or arrival in wrong location Other mistakes of shippers could happen since they are not professional employees The customers’ co-creation behavior in terms of tolerance may also refer to their acceptance level of these possible small mistakes of the amateur shippers

The dimension of advocacy in this research directly adopts items from model of

Yi & Gong (2013) AD4 is the added item from the observation that customer could encourage of service usage by sharing order with other customers

Table 3.2 Questions of local delivery service quality

Q2 Order is delivered on time

Q3 Order is delivered in good condition

Q6 Shipper has proper equipment to preserve food/drinks

Q7 Using this service helps you to save money

In terms of measure items for service quality of crowd local food delivery, the first item reflect the main value proposition of this kind of service “speed” (Carbone et al., 2017) and translation from customer’s perspective could be “fast shipping time”

The items Q2, Q3, Q4 and Q 7 are adopted from operational performance and cost performance in service quality model of Stank et al (2003) Q8 is a new item of operational aspect of service quality In this new kind of service, the service encounter is almost virtual via mobile application interface Therefore, the performance of the application is one of the important aspect of operational quality of the service

As suggestion from the research of Rao et al (2011) with application of this model from B2B to B2C context, dimension of relational performance is less relevant

The further development of other items of service quality of crowd local food delivery service comes from the dimensions of SERVQUAL (Parasuraman et al., 1988) Q5 and Q6 adopt items of tangibles and assurance in relation with shipper The final Q9 is taken from the suggestion of physical distribution literature (T Mentzer et al.,

2001) as the importance of service availability Hence, the wide possible selection of restaurant and meal is also an aspect of quality of this kind of model.

Research method

This research applies quantitative strategy with survey method The question items are taken from the applied literature with essential customization and adjustment to fit into the service context and setting of crowd local food delivery

Due to scope limitation of this research, only the type of food delivery is considered

The survey was designed with Google Form and distributed via Internet Link of the survey form was sent through email or shared directly in social networks

Besides demographic questions, respondents were asked to evaluate each statement in 5-point Likert scale Google Form service helps automatically receive and record responses

In the survey, there is explanation helps respondents have clear distinction between normal food delivery service and crowd local food delivery service Later, respondents have to confirm whether they use the right type of service for this research If they answer ‘No’, the survey will be terminated Therefore the reliability of the survey is assured

The survey was sent to the most potential service users via email or social networks The major types of targeting respondents are students of Vietnam Maritime University, students of VinFast Vocational School, and ‘big four’ international auditing companies in Vietnam.

DATA ANALYSIS AND FINDINGS

Data collection and demographic results

From 23 rd of May to 30 th of May, 2019 there are 196 responses from Google Form However, after removing the responses with same points for all the questions, there are only 180 valid responses left Because of the survey design, respondents could only choose answers from 1 to 5 Hence, there are no responses with out of range answer

The number of remaining responses is sufficient for further analysis As the total observed variables are 29, independent variables are 4, 180 responses are greater than:

 50 + 8*4 = 90 as minimum number of responses for multiple linear regression (Tabachnick, Fidell, & Ullman, 2007)

 29*5 = 145 as minimum number of responses for exploratory factor analysis (Bollen, 1989) (Hair, Black, Babin, & Anderson, 2010)

Among respondents, 114 people are female and only 66 people are male It means that nearly two third of respondents are female Women are certainly interested in food ordering than men

Table 4.1 Gender of respondents (Processed by SPSS 24)

More than 70% of respondents are between 18 and 25-year-old The respondents between 26 and 35-year-old take account of 26.1% There are only few respondents who are less than 18-year-old or over 36-year-old

Table 4.2 Age distribution of respondents (Processed by SPSS 24)

60% of respondents have already graduated from high school, while 18.3% did finish university or college Nearly 22% of respondents are masters or doctors

Table 4.3 Education level of respondents (Processed by SPSS 24)

Most of respondents are living in Haiphong city, equal 80% of total respondents

Thirty respondents are living in Hanoi, while only 2.8% of them in Ho Chi Minh City

Table 4.4 Living location of respondents (Processed by SPSS 24)

About respondents’ most frequently used crowd food delivery service, NOW (Foody) takes account for almost 79% It is reasonable since majority of respondents are living in Haiphong in which NOW (Foody) dominates the market

Table 4.5 Most frequently used service (Processed by SPSS 24)

Reliability test

Applying Cronbach’s α, a scale is accepted if Cronbach α ≥ 0.6 (Nunnally &

Bernstein, 1994) A scale with Cronbach’s α among [0.75; 0.95] has good reliability

Furthermore, in SPSS, an observed variable that has corrected item-total correlation

4.2.1 Reliability analysis of Responsible behavior

Table 4.6 Testing reliability of Responsible behavior (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

According to the above testing results, the scale of responsible behavior has good reliability with Cronbach’s α equal 0.775 and all observed variables remain in the scale with corrected item-total correlations are higher than 0.3 No item leads to increase of Cronbach’s α if it is deleted

Table 4.7 Testing reliability of Feedback (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

It could lead to considerable increase of Cronbach’s α if deleting FB1 Therefore, reliability is re-tested

Table 4.8 Re-testing reliability of Feedback 1 (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Again, FB4 should be removed in order to increase Cronbach’s α from 0.808 to 0.820

Table 4.9 Re-testing reliability of Feedback 2 (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Table 4.10 Testing reliability of Tolerance (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Item TO4 should be deleted in order to increase Cronbach’s α from 0.809 to 0.834

Table 4.11 Re-testing reliability of Tolerance (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Table 4.12 Testing reliability of Advocacy (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Similarly, deleting item AD4 could increase Cronbach’s α from 0.731 to 0.761

Table 4.13 Re-testing reliability of Advocacy (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Table 4.14 Testing reliability of Quality (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Deleting item Q7 would increase the Cronbach’s α by a small margin After deleting this item, Q9 changes its value of “Cronbach’s alpha if item deleted” to 0.866

Eventually, deleting both Q7 and Q9 helps to improve Cronbach’s α to 0.866 as the following table

Table 4.15 Re-testing reliability of Quality (Processed by SPSS 24)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Factor analysis

In order to test the convergent validity and discriminant validity, exploratory factor analysis is implemented (Nguyen, 2013) All the remaining observed items are assigned to EFA process

Table 4.16 KMO and Bartlett's test (Processed by SPSS 24)

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .821 Bartlett's Test of Sphericity Approx Chi-Square 1763.984 df 253

KMO’s test (Kaiser – Meyer – Olkin measure of sampling adequacy) with value of 0.821 that is greater than 0.80 or the threshold of good test (Kaiser, 1974) Sig of Bartlett’s Test of Sphericity is 0.000 and less than 0.05, thus it is accepted (Nguyen,

In order to achieve higher extraction, PCA (Principal Components Analysis model) is chosen extraction method instead of CFM (Common Factor model) (Kim

& Mueller, 1978) Further pursuing this purpose, Varimax is applied for rotation method (Hair et al., 2010) Based on the research model, number of factors is set at

5 The scores that has absolute values less than 0.50 are deleted

Table 4.17 EFA rotated component matrix (Processed by SPSS 24)

Extraction Method: Principal Component Analysis

Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 6 iterations

In this EFA model, cumulative extraction sums of squared loadings is 60.500% that is greater than 60% Therefore, this is a good EFA model (Nguyen, 2013).

Correlation test

Based on the result of EFA, the author creates six representative variables with the following computing values:

 Quality (representing dependent variable) = Mean (Q1, Q2, Q3, Q4, Q5, Q6, Q8)

 RB (representing independent variable of Responsible behavior) = Mean (RB1, RB2, RB3, RB4, RB6, RB7)

 FB (representing independent variable of Feedback) = Mean (FB2, FB3)

 Tolerance (representing independent variable of Tolerance) = Mean (TO1, TO2, TO3)

 AD (representing independent variable of Advocacy) = Mean (AD2, AD3)

Based on the following table, all independent variables have linear correlations with dependent variable

Table 4.18 Correlations (Processed by SPSS 24)

Quality RB FB Tolerance AD Quality Pearson

** Correlation is significant at the 0.01 level (2-tailed).

Regression

Applying linear regression with Enter method, the result as the following:

Table 4.19 Regression model summary (Processed by SPSS 24)

Std Error of the Estimate

1 544 a 296 280 56702 1.830 a Predictors: (Constant), AD, RB, FB, Tolerance b Dependent Variable: Quality With Adjusted R Square of 0.280, the independent variables only could explain 28% of dependent variable of “Quality” The value of Durbin-Watson is 1.830 < 2, co-creation process, this not great value of R Square and Adjusted R Square is reasonable The service quality should be explained by other aspects especially the co-creation of the platform and individual shipper

Table 4.20 Regression coefficients (Processed by SPSS 24)

Because of sig of RB (Responsible behavior) and FB (Feedback) are greater than 0.05, the author could not accept or reject hypothesis H1, H2

Independent variable of “Tolerance” has sig (equal 0.000) less than 0.05 and standardized coefficients of 0.291, thus Tolerance affects positively the service quality Hypothesis H3 is accepted

Independent variable of “Advocacy” has sig (equal 0.001) less than 0.05 and standardized coefficients of 0.265, thus Advocacy affects positively the service quality Hypothesis H4 is accepted

All VIF values are less than 2.20, hence there are no violations of multicollinearity (Nguyen, 2013).

Findings and implications

Both Tolerance and Advocacy are dimensions of customer citizenship behavior or they are behaviors of extra-role of customer in value co-creation process The data analysis result proves that crowd local food delivery service quality is partly influenced by these behaviors from customer Therefore, the platform service provider such as Grab, NOW or Go-Food should take more efforts to link customer to overall value proposition of the whole platforms rather than just direct value proportion between each customer and crowd service providers

While Tolerance shows customer’s understanding of the this crowd logistics initiative, Advocacy presents customer’s belief in the sustainable benefit of the service model As a result, platform service provider should not just only focus on operational issues and the in-role of customer, but expand the integration of customer into the whole service system that connect them to other co-creators such as crowd shippers and restaurants

The integration towards the whole service platforms concerns more about the social value among different value co-creators The crowd service model should carry more social value proportion instead of solely economic and individual one This is actually suggested by the study of Carbone et al (2017) Furthermore, some research such as Frasquet-Deltoro et al (2019) has already hinted the more impact from citizenship behavior than participation behavior.

CONCLUSION

Contributions

This research succeeds validating scale for customer co-creation behavior in a new and specific service model While the previous researches on this topic are mostly conceptual or just general model among various kind of services

The research also contribute significantly to understanding of crowd local delivery service in terms of relevant dimensions of customer co-creation behavior and service quality The researches on this kind of crowd logistics service are still very limited Traditional service quality models in B2B and B2C in bricks and mortar business do not fit this service well with service counter is more on the digital and virtual world

The scales of customer co-creation behavior and service quality of the crowd local food delivery are not just useful for academic researchers but also very important for practical business Based on these scales, businesses could evaluate customer co-creation behavior and the service quality They could understand weakness and strengths of customer co-creation behavior in their crowd local food delivery business They also could focus on improving co-creation behavior of customer in terms of voluntary aspects rather than in-role perspectives.

Limitations

The focus is on the crowd local delivery service; however, the research has just attempted to deal with one type of it – the food delivery Even the two share similar characteristics, the differences in service delivery process may lead to different relevant dimensions of customer co-creation behavior

The respondents are almost living in Haiphong city in which there could be many different service contexts in comparison with much larger city such as Hanoi or Ho Chi Minh City

The respondents answer both question items of independent and dependent variable This is another limitation of the research as it could lead to common bias.

Future research

Based on the findings of this research, further studies could be implemented in regards to all involved co-creators instead of only customer Both researches on local parcel delivery and food delivery could explore more influenced factors and possible moderators More possible consequences of value co-creation should be investigated, too

From the verified observed variables of the service quality, a more dedicated research on dimensions of service quality for the new kind of services should be considered.

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Survey form in both Vietnamese and English

Appendix 1 Survey form in both Vietnamese and English

Khảo sát về dịch vụ giao đồ ăn theo mô hình đám đông

Survey of crowd local food delivery service

Tôi đang tiến hành nghiên cứu về dịch vụ giao đồ ăn theo mô hình đám đông như NOW, GrabFood, Go-Food Cảm ơn bạn đã đồng ý tham gia khảo sát này

I am researching on crowd local food delivery service such as NOW, GrabFood, Go-Food… Thank you for agreeing to participate this survey

Bạn sẽ chỉ mất khoảng hơn 10 phút để hoàn thành bảng câu hỏi dưới đây Hãy trả lời theo đúng cảm nhận của bạn về dịch vụ giao đồ đồ ăn theo mô hình đám đông mà bạn đang sử dụng

It takes only around 10 minutes completing the following questionnaire Please answer based on your opinions about crowd local food delivery service that you are using

Thông tin cá nhân của bạn sẽ được Tôi bảo mật tuyệt đối, tất cả các phản hồi và thông tin mà bạn cung cấp sẽ chỉ được sử dụng cho mục đích nghiên cứu

Your personal information will be absolutely secured All the reponses and information from you are only used for research purpose

Chúc bạn luôn vui vẻ !!!

Bạn có sử dụng dịch vụ giao đồ ăn theo mô hình đám đông tương tự như NOW (Foody), GrabFood hay Go Food không?

Do you use crowd local food delivery service such as NOW (Foody), GrabFood or Go Food?

 Có [chuyển tiếp tới các câu hỏi tiếp theo] (Yes – shifting to the next questions)

 Không [kết thúc khảo sát] (No – end of survey)

Bạn vui lòng cung cấp các thông tin chung sau đây về mình

Please providing the following general information about yourself

 Nữ (Female) Độ tuổi (Age):

 Trên 45 (More than 45) Trình độ học vấn hiện tại của bạn (Your current education level):

 Sau đại học (Post-graduate)

 Tốt nghiệp đại học, cao đẳng (Graduate)

 Chưa tốt nghiệp cấp 3 (Under high school) Bạn đang là (Your employment status):

 Working Bạn đang sống ở (Your current living location):

 TP Hồ Chí Minh (Ho Chi Minh city)

Dịch vụ giao đồ ăn theo mô hình đám đông mà bạn sử dụng thường xuyên nhất (Your most frequent used crowd local food delivery):

Bạn vui lòng cho biết mức độ tán đồng với các nhận định sau liên quan tới việc bạn sử dụng dịch vụ giao đồ ăn , trong đó 1= Hoàn toàn KHÔNG đồng ý, 5= Hoàn toàn đồng ý

Please, providing your level of agreement on the following statement regarding to your use of crowd local food delivery service 1= Totally disagree, 5= Totally agree

1 Bạn cung cấp chính xác địa điểm giao hàng

You provide accurate delivery address

2 Bạn mô tả đầy đủ yêu cầu đặt hàng

You provide sufficient order information

3 Bạn cung cấp thông tin cần thiết để người giao hàng đến đúng nơi giao hàng

You provide appropriate information for shipper to deliver to the right place

4 Bạn trả lời tất cả câu hỏi của người giao hàng khi họ hỏi về yêu cầu giao hàng

You answer all order-related questions

5 Bạn thu xếp để ra nhận hàng đúng hẹn

You manage to be available at the delivered location on time

6 Bạn để ý tới điện thoại để có thể nhận cuộc gọi của người giao hàng

You pay attention to the mobilephone in order to receive the shipper's call

7 Đối với bạn, việc ra nhận hàng đúng hẹn quan trọng

Arriving at the receiving place on time is important to your

8 Bạn không hủy đơn hàng khi người giao hàng đã đi lấy đơn hàng bạn đặt

You do not cancel order when shipper is leaving for it

9 Tốc độ giao hàng nhanh chóng

10 Đơn hàng được giao đúng hẹn

Order is delivered on time

11 Đơn hàng được giao trong tình trạng tốt

Order is delivered in good conditions

12 Món ăn/uống được giao chính xác theo đơn hàng

13 Người giao hàng có thái độ lịch sự

14 Người giao hàng có phương tiện bảo quản hàng giao phù hợp

Shipper has proper equipment to preserve food/drinks

15 Sử dụng dịch vụ này giúp bạn tiết kiệm chi phí

Using this service helps you to save money

16 Ứng dụng giao đồ ăn hoạt động trơn tru

17 Món ăn/uống bạn có thể đặt rất phong phú

18 Bạn thông báo lại những vấn đề gặp phải trong quá trình sử dụng dịch vụ

You inform issues during using service

19 Bạn cho rằng việc đánh giá (rating) người giao hàng là cần thiết

Rating shipper is important to you

20 Bạn thực hiện đánh giá người giao hàng mỗi lần sử dụng dịch vụ

You do rating each time using service

21 Khi bạn nhận được dịch vụ tốt từ người giao hàng, bạn đánh giá (rating) cao để khen ngợi họ

You are patient when shipper is late

23 Nếu người giao hàng đến nhầm địa điểm, bạn chờ họ giao lại

If shipper goes to wrong place, you wait for rerouting

24 Bạn sẵn lòng bỏ qua sai sót của người giao hàng

You are willing to forgive shipper's mistakes

25 Bạn cho rằng việc người giao hàng mắc sai sót là bình thường

You suppose that shipper's mistake is ordinary

26 Bạn nhận xét tốt về dịch vụ giao đồ ăn bạn sử dụng trước những người khác

You review positively about the service to others

27 Bạn giới thiệu dịch vụ giao đồ ăn này tới người khác

You recommend this service to others

28 Bạn khuyến khích mọi người sử dụng dịch vụ giao đồ ăn này

You encourage others using this service

29 Bạn rủ người khác cùng đặt đơn hàng chung

You invite others to share order

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