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.
Ahn, J., Lee, C.-K., Back, K.-J., & Schmitt, A (2019) Brand experiential value for creating integrated resort customers’ co-creation behavior International Journal of Hospitality Management, 81, 104-112 Retrieved from http://www.sciencedirect.com/science/article/pii/S0278431918308983 doi:https://doi.org/10.1016/j.ijhm.2019.03.009
Bendapudi, N., & Leone, R P (2003) Psychological Implications of Customer
Participation in Co-Production Journal of Marketing, 67(1), 14-28 Retrieved from https://doi.org/10.1509/jmkg.67.1.14.18592 doi:10.1509/jmkg.67.1.14.18592
Bienstock, C C., Mentzer, J T., & Bird, M M (1997) Measuring physical distribution service quality Journal of the Academy of marketing Science, 25(1), 31 Retrieved from https://doi.org/10.1007/BF02894507 doi:10.1007/BF02894507
Bollen, K A (1989) A new incremental fit index for general structural equation models Sociological Methods & Research, 17(3), 303-316
Cantone, L., Testa, P., & Marrone, T (2019) Service-Dominant Logic: Inward and
Outward Views In P P Maglio, C A Kieliszewski, J C Spohrer, K Lyons,
L Patrício, & Y Sawatani (Eds.), Handbook of Service Science, Volume II (pp
Carbone, V., Rouquet, A., & Roussat, C (2017) The Rise of Crowd Logistics: A
New Way to Co-Create Logistics Value Journal of Business Logistics, 38(4),
238-252 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1111/jbl.12164 doi:10.1111/jbl.12164
Cronin Jr, J., & Taylor, S (1992) Measuring Service Quality - A Reexamination And
Di Gangi, P M., & Wasko, M (2009) Steal my idea! Organizational adoption of user innovations from a user innovation community: A case study of Dell IdeaStorm Decision support systems, 48(1), 303-312
Edvardsson, B., Tronvoll, B., & Gruber, T (2011) Expanding understanding of service exchange and value co-creation: a social construction approach
Journal of the Academy of marketing Science, 39(2), 327-339 Retrieved from https://doi.org/10.1007/s11747-010-0200-y doi:10.1007/s11747-010-0200-y
Ennew, C., & Binks, M (1999) Impact of Participative Service Relationships on
Quality, Satisfaction and Retention: An Exploratory Study (Vol 46)
Firat, A F., & Venkatesh, A (1995) Liberatory Postmodernism and the
Reenchantment of Consumption Journal of Consumer Research, 22(3), 239-
267 Retrieved from https://doi.org/10.1086/209448 doi:10.1086/209448
Frasquet-Deltoro, M., Alarcón-del-Amo, M.-d.-C., & Lorenzo-Romero, C (2019)
Antecedents and consequences of virtual customer co-creation behaviours
Internet Research, 29(1), 218-244 Retrieved from https://www.emeraldinsight.com/doi/abs/10.1108/IntR-06-2017-0243 doi:doi:10.1108/IntR-06-2017-0243
Fuat Firat, A., Dholakia, N., & Venkatesh, A (1995) Marketing in a postmodern world European Journal of Marketing, 29(1), 40-56 Retrieved from https://www.emeraldinsight.com/doi/abs/10.1108/03090569510075334 doi:doi:10.1108/03090569510075334
Galvagno, M., & Dalli, D (2014) Theory of value co-creation: a systematic literature review Managing Service Quality, 24(6), 643-683
Grửnroos, C (2008a) Adopting a service business logic in relational business-to- business marketing: value creation, interaction and joint value co-creation
Paper presented at the Otago Forum
Grửnroos, C (2008b) Service logic revisited: who creates value? And who co‐ creates? European Business Review, 20(4), 298-314 Retrieved from https://www.emeraldinsight.com/doi/abs/10.1108/09555340810886585 doi:doi:10.1108/09555340810886585
Grửnroos, C (2012) Conceptualising value co-creation: A journey to the 1970s and back to the future (Vol 28)
Grửnroos, C., & Ravald, A (2011) Service as business logic: implications for value creation and marketing Journal of Service Management, 22(1), 5-22
Retrieved from https://www.emeraldinsight.com/doi/abs/10.1108/09564231111106893 doi:doi:10.1108/09564231111106893
Grửnroos, C., & Voima, P (2013) Critical service logic: making sense of value creation and co-creation Journal of the Academy of marketing Science, 41(2), 133-150 Retrieved from https://doi.org/10.1007/s11747-012-0308-3 doi:10.1007/s11747-012-0308-3 Groth, J., & Dye, R (1999) Service quality: Perceived value, expectations, shortfalls, and bonuses (Vol 9)
Groth, M (2005) Customers as Good Soldiers: Examining Citizenship Behaviors in
Gulc, A (2017) Models and Methods of Measuring the Quality of Logistic Service
Procedia Engineering, 182, 255-264 Retrieved from http://www.sciencedirect.com/science/article/pii/S1877705817313231 doi:https://doi.org/10.1016/j.proeng.2017.03.187
Gummesson, E (2007) Exit services marketing-enter service marketing Journal of customer behaviour, 6(2), 113-141
Gummesson, E (2008) Customer centricity: reality or a wild goose chase? European
Business Review, 20(4), 315-330 Retrieved from https://doi.org/10.1108/09555340810886594 doi:10.1108/09555340810886594
Gustafsson, A., Kristensson, P., & Witell, L (2012) Customer co-creation in service innovation: a matter of communication? Journal of Service Management, 23(3), 311-327
Hair, J., Black, W C., Babin, B J., & Anderson, R E (2010) Multivariate data analysis: International version New Jersey, Pearson
Hau, L N., Tram Anh, P N., & Thuy, P N (2017) The effects of interaction behaviors of service frontliners on customer participation in the value co- creation: a study of health care service Service Business, 11(2), 253-277
Retrieved from https://doi.org/10.1007/s11628-016-0307-4 doi:10.1007/s11628-016-0307-4
Heinonen, K., Strandvik, T., Mickelsson, K J., Edvardsson, B., Sundstrửm, E., &
Andersson, P (2010) A customer‐dominant logic of service Journal of Service Management, 21(4), 531-548 Retrieved from https://www.emeraldinsight.com/doi/abs/10.1108/09564231011066088 doi:doi:10.1108/09564231011066088
Hienerth, C., Keinz, P., & Lettl, C (2011) Exploring the nature and implementation process of user-centric business models Long Range Planning, 44(5-6), 344-
Hussainy, K K S K (2017) Dimensions of Customer Value Co-Creation Behavior in a Service Setting Journal of Managerial Sciences, 11(03), 83-96
Jim, S., Laura, A., Norm, P., & Tryg, A (2008) Service science and service- dominant logic Otago Forum, 2, 4-18 Retrieved from www.business.otago.ac.nz/Marketing/Events/OtagoForum/Final%20forum%
20papers/Otago%20Forum%20Paper%202_Spohrer.pdf
Juliet, S (2014) Debating the Sharing Economy Great Transition Initiative
Retrieved from https://www.greattransition.org/publication/debating-the- sharing-economy
Karpen, I O., Bove, L L., & Lukas, B A (2012) Linking service-dominant logic and strategic business practice: A conceptual model of a service-dominant orientation Journal of service research, 15(1), 21-38
Knoblich, G., Butterfill, S., & Sebanz, N (2011) Psychological Research on Joint
Action Theory and Data (Vol 54)
Lusch, R., & E Webster, F (2011) A Stakeholder-Unifying, Cocreation Philosophy for Marketing (Vol 31)
Lusch, R F (2006) The Small and Long View Journal of Macromarketing, 26(2),
240-244 Retrieved from https://doi.org/10.1177/0276146706291045 doi:10.1177/0276146706291045
Lusch, R F (2011) Reframing supply chain management: a service-dominant logic perspective Journal of Supply Chain Management, 47(1), 14-18 Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1745- 493X.2010.03211.x doi:10.1111/j.1745-493X.2010.03211.x
Lusch, R F., & Vargo, S L (2014a) Evolving to a new dominant logic for marketing
In The Service-Dominant Logic of Marketing (pp 21-46): Routledge
Lusch, R F., & Vargo, S L (2014b) Service-dominant logic: Premises, perspectives, possibilities: Cambridge University Press
Lusch, R F., Vargo, S L., & Wessels, G (2008) Toward a conceptual foundation for service science: Contributions from service-dominant logic IBM systems journal, 47(1), 5-14
Maglio, P P., & Spohrer, J (2008) Fundamentals of service science Journal of the
McColl-Kennedy, J R., Vargo, S L., Dagger, T S., Sweeney, J C., & Kasteren, Y v (2012) Health care customer value cocreation practice styles Journal of service research, 15(4), 370-389
Mehmann, J., Frehe, V., & Teuteberg, F (2015) Crowd Logistics − A Literature
Mentzer, J T., Gomes, R., & Krapfel, R E (1989) Physical Distribution Service: A
Fundamental Marketing Concept? Journal of the Academy of marketing
Science, 17(1), 53-62 Retrieved from https://journals.sagepub.com/doi/abs/10.1177/009207038901700107
Nambisan, S., & Nambisan, P (2008) How to Profit from a Better Virtual Customer
Neghina, C., Caniởls, M C., Bloemer, J M., & van Birgelen, M J (2015) Value cocreation in service interactions: Dimensions and antecedents Marketing theory, 15(2), 221-242
Nguyen, D T (2013) Phương pháp nghiên cứu khoa học trong kinh doanh In (2nd ed.) Ho Chi Minh city, Vietnam: Finance publishing house
Normann, R., & Ramirez, R (1993) From value chain to value constellation:
Designing interactive strategy Harvard business review, 71(4), 65-77
Parasuraman, A., Zeithaml, V A., & Berry, L L (1988) Servqual: A multiple-item scale for measuring consumer perc Journal of retailing, 64(1), 12
Porter, M E (2008) Competitive advantage: Creating and sustaining superior performance: Simon and Schuster
Rafiq, M., & Jaafar, H S (2007) Measuring customers' perceptions of logistics service quality of 3pl service providers Journal of Business Logistics, 28(2), 159-175 Retrieved from https://doi.org/10.1002/j.2158-1592.2007.tb00062.x doi:10.1002/j.2158-1592.2007.tb00062.x
Ramaswamy, V., & Prahalad, C K (2004) Co‐creating unique value with customers Strategy & Leadership, 32(3), 4-9 Retrieved from https://doi.org/10.1108/10878570410699249 doi:10.1108/10878570410699249
Randall, W S., Gravier, M J., & Prybutok, V R (2011) Connection, trust, and commitment: dimensions of co-creation? Journal of strategic marketing, 19(01), 3-24
Rao, S., Goldsby, T J., Griffis, S E., & Iyengar, D (2011) Electronic Logistics
Service Quality (e-LSQ): Its Impact on the Customer’s Purchase Satisfaction and Retention Journal of Business Logistics, 32(2), 167-179 Retrieved from https://doi.org/10.1111/j.2158-1592.2011.01014.x doi:10.1111/j.2158- 1592.2011.01014.x
Rinehart, L M., Cooper, M B., & Wagenheim, G D (1989) Furthering the
Integration of Marketing and Logistics Through Customer Service in the Channel Journal of the Academy of marketing Science, 17(1), 63-71
Retrieved from https://journals.sagepub.com/doi/abs/10.1177/009207038901700108 doi:10.1177/009207038901700108 Ritzer, G., & Jurgenson, N (2010) Production, Consumption, Prosumption: The nature of capitalism in the age of the digital ‘prosumer’ Journal of Consumer
Culture, 10(1), 13-36 Retrieved from https://doi.org/10.1177/1469540509354673 doi:10.1177/1469540509354673
S Ohern, M., & Rindfleisch, A (2010) Customer Co-Creation: A Typology and
Research Agenda In (Vol 6, pp 84-106)
Saarijọrvi, H., Kannan, P., & Kuusela, H (2013) Value co-creation: theoretical approaches and practical implications European Business Review, 25(1), 6-
Schenk, E., & Guittard, C (2011) Towards a characterization of crowdsourcing practices (Vol n°7)
Stank, T P., Goldsby, T J., & Vickery, S K (1999) Effect of service supplier performance on satisfaction and loyalty of store managers in the fast food industry Journal of Operations Management, 17(4), 429-447 Retrieved from http://www.sciencedirect.com/science/article/pii/S0272696398000527 doi:https://doi.org/10.1016/S0272-6963(98)00052-7
Stank, T P., Goldsby, T J., Vickery, S K., & Savitskie, K (2003) Logistics service performance: Estimating its influence on market share Journal of Business Logistics, 24(1), 27-55 Retrieved from https://doi.org/10.1002/j.2158- 1592.2003.tb00031.x doi:10.1002/j.2158-1592.2003.tb00031.x
T Mentzer, J., Flint, D., & Hult, T (2001) Logistics Service Quality as a Segment-
Tabachnick, B G., Fidell, L S., & Ullman, J B (2007) Using multivariate statistics
Thai, V (2013) Logistics service quality: Conceptual model and empirical evidence
Tommasetti, A., Troisi, O., & Vesci, M (2017) Measuring customer value co- creation behavior: Developing a conceptual model based on service-dominant logic Journal of Service Theory and Practice, 27(5), 930-950
Vargo, S L., & Lusch, R F (2008) Service-dominant logic: continuing the evolution
Journal of the Academy of marketing Science, 36(1), 1-10
Vargo, S L., & Lusch, R F (2011) Service‐dominant logic: a necessary step
European Journal of Marketing, 45(7/8), 1298-1309 Retrieved from https://doi.org/10.1108/03090561111137723 doi:10.1108/03090561111137723 Vargo, S L., & Lusch, R F (2016) Institutions and axioms: an extension and update
5-23 Retrieved from https://doi.org/10.1007/s11747-015-0456-3 doi:10.1007/s11747-015-0456-3
Wieland, H., Polese, F., Vargo, S., & Lusch, R (2014) Toward a Service
(Eco)Systems Perspective on Value Creation (Vol 3)
Yi, Y., & Gong, T (2013) Customer value co-creation behavior: Scale development and validation Journal of Business Research, 66(9), 1279-1284
Yi, Y., Nataraajan, R., & Gong, T (2011) Customer participation and citizenship behavioral influences on employee performance, satisfaction, commitment, and turnover intention Journal of Business Research, 64(1), 87-95 Retrieved from http://www.sciencedirect.com/science/article/pii/S0148296309003178 doi:https://doi.org/10.1016/j.jbusres.2009.12.007
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