aspects: (1) This study develops a value co-creation measurement scalethat consists of participation and partnership value co-creation di-mensions. (2) To distinguish the factor structure of the participationand partnership activities, this study enhances the extant impact-asymmetry analysis developed by Mikulic and Prebezac (2008) by in-troducing Partial Least Square (PLS) analysis to assess the formativemeasurement model. (3) Although the results of Mikulic and Prebezac’simpact-asymmetry analysis assist service managers in prioritizing theimprovement of service attributes, the extant impact-asymmetry ana-lysis methods do not provide the overarching strategic actions as a ty-pical importance-performance analysis (IPA). This study formulatesstrategic actions for attributes in different factor categories to design animpact-asymmetry analysis. (4) This study attempts to make a con-tribution by integrating the three-factor theory into the value co-crea-tion theory. Since most of the previous studies of value co-creation onlydescribed the linear relationships between value co-creation factors andtheir consequences, some important asymmetry factors might havebeen overlooked. The combination of three-factor and value co-creationtheories extends our knowledge in classifying and prioritizing sym-metry and asymmetry factors of value co-creation to strategically in-crease the value of co-creation processes.2. Literature review2.1. Three-factor theory and impact-asymmetry analysisThe three-factor theory of customer satisfaction (Kano et al., 1984)presumes that the influence of a product/service attribute on overallcustomer satisfaction varies based on its performance. The three-factortheory suggests that attributes can be categorized into three factors:basic, excitement, and performance. As shown in Fig. 1, basic factorscause great dissatisfaction (in the left lower quadrant) if not fulfilledand have little influence on overall satisfaction (in the right lowerquadrant) even when implemented (Anderson and Mittal, 2000). Ex-citement factors show a more significant impact on satisfaction (in theright upper quadrant) when implemented and do not trigger dis-satisfaction (in the left upper quadrant) when absent (Lee and Min,2013). Therefore, a negative or positive asymmetric relationship existsbetween a product/service attribute and overall customer satisfactionwhen the product/service is basic or exciting. Performance factorscreate both satisfaction (in the right upper quadrant) and dissatisfaction(in the left lower quadrant); therefore, they show a symmetric link tosatisfaction (Matzler et al., 2004).Based on the symmetric and asymmetric nature of these three fac-tors, few quantitative methods have been developed to identify thefactor structure of product/service attributes. A common method is thepenalty-reward contrast analysis developed by Brandt (1987). In thismethod, a reward index and a penalty index are generated by a multipleregression analysis with two sets of dummy variables. Eq. (1) shows abasic formula to calculate the reward and penalty indices for a researchmodel with only one attribute. The researcher then compared the va-lues of the reward and penalty indices to classify the factor structure ofthe attribute. If the value of the reward index of an attribute is largerthan the value of its penalty index, the attribute is an excitement factor;alternatively, if the value of the reward index of an attribute is smallerthan the value of its penalty index, the attribute is a basic factor; and, ifthe value of the reward index of an attribute is approximately equal tothe value of its penalty index, the attribute is a performance factor.= + × +× +OS C reward index reward dummy penalty indexpenalty dummy error_ _ __ (1)where OS=overall satisfaction and C=constant.Recently, Mikulic and Prebezac (2008) extended the penalty-rewardcontrast analysis for assessing the asymmetric range of an attribute’simpact on satisfaction; namely, impact range-performance analysis(IRPA) coupled with impact-asymmetry (IA) analysis. They suggestedthat when establishing priorities for improving an attribute, we shouldfirst consider its range of impact on overall satisfaction (RIOS) (Eq. (2))and then compare its satisfaction-generating potential (SGP) (Eq. (3)) toits dissatisfaction-generating potential (DGP) (Eq. (4)). When the SGP isgreater than the DGP, the attribute is a satisfier. Alternatively, when theSGP is less than the DGP, the attribute is a dissatisfier. They suggestedusing a value that is referred as to IA (Eq. (5)) for quantifying theasymmetry of an attribute’s impact on overall satisfaction.= +RIOS rewardindex penaltyindex (2)=SGPrewardindexRIOS (3)=DGPpenaltyindexRIOS (4)= −IA SGP DGP (5)Mikulic and Prebezac (2008) further suggested subdividing IA intofive categories based on the degree of asymmetry of its impact onoverall satisfaction to reflect extremely low and extremely high per-formance. The five categories are: (1) “delighters” (IA > 0.6), (2)“satisfiers” (0.6≥ IA> 0.2), (3) “hybrids” (0.2≥ IA≥−0.2), (4)“dissatisfiers” (−0.2 > IA≥−0.6), and (5) “frustrators” (IA< −0.6)(Mikulic and Prebezac, 2011). In addition, to facilitate a distinctionbetween more or less relevant attributes in the creation of overall sa-tisfaction, the attributes were also subdivided into three categoriesbased on their RIOS, referred to as the impact range (IR), as follows: (a)“high-impact attributes” (RIOS > 0.225), (b) “medium-impact attri-butes” (0.125≤ RIOS≤ 0.225), and (c) “low-impact attributes”(RIOS < 0.125). A graph is plotted using IR as the x-axis and IA as they-axis to classify the attribute into fifteen quadrants, as shown in Fig. 2.Based on the attributes’ positions in the graph, Mikulic and Prebezac(2008, 2011) suggested that service managers can make decisionsconcerning improvement priorities of service attributes. However, theyhave not provided corresponding strategic actions for attributes in eachquadrant of the impact-asymmetry analysis.For the measurement of impact-asymmetry analysis, Mikulic andPrebezac (2008) used nine single-item measures for evaluating theservices at a major Croatian airport; Coghlan (2012) employed 19single-item measures for evaluating four types of trip attributes at theGreat Barrier Reef Marine Park in Queensland, Australia; Mikulic andPrebezac (2011) selected 16 single-item measures for evaluating threetypes of hotel animation programs at Mediterranean sun-and-sea re-sorts; and Back (2012) employed 17 single-item measures for evalu-ating four types of services at Korean restaurants in the United States.The researchers only applied single-item measures for a factorFig. 1. Kano's model of customer satisfaction (adapted from Kano et al., 1984).J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131119
(construct) in the previous studies. However, single-item measures donot allow for measurement error adjustment, and this generally de-creases their reliability and causes lower predictive validity (Hair et al.,2017). Thus, to increase their reliability and predictive validity, it issuggested that multiple items be used to measure a construct. The lit-erature review only showed very little reference to using multipleitems. Most recently, Mikulic et al. (2015) revealed a five-dimensionalstructure of the yachting tourism experience and found three out of fiveexperience dimensions have a significantly asymmetrical influence onthe overall yachting experience. However, their study was not used aformative measurement scale in the impact-asymmetry analysis.2.2. Value co-creation activities in exhibitionsAn exhibition is a major form of MICE (meetings, incentives, con-ferences, and exhibitions) events, and it is one of the main componentsof the tourism industry (Whitfield et al., 2014). The co-creation of valueis a desirable goal as it can assist firms in highlighting the customers’points of view and improving the front-end process of identifying cus-tomers’ needs and wants (Lusch and Vargo, 2006). Unlike other hos-pitality industries that primarily involve two parties (firms and custo-mers), exhibitions involve three parties: organizers, exhibitors, andvisitors. In other hospitality business sectors, only the customers arebeing served. However, the roles of exhibitors in an exhibition are morecomplex. They are being served by the organizer and they are alsodelivering services to visitors. This provides them a stronger reason towork closely with the organizer in value co-creation activities (Dwyerand Forsyth, 1997; Mistilis and Dwyer, 1999). Hence, in an exhibition,the exhibition organizer (firm) and exhibitors (customers) commu-nicate and cooperate with each other closely to make the exhibitionsuccessful (Jin and Weber, 2013). Together, the exhibitors and the or-ganizer have an opportunity to create value through the value co-creation activities of producing and delivering an exhibition. Exhibitorsperform a series of value co-creation activities to assist the organizerand themselves in obtaining the best outcome of the exhibition. Thesevalue co-creation activities can be generally divided into two types:participation and partnership activities.2.2.1. Participation activitiesParticipation activities refer to “the degree to which the customer isinvolved in producing and delivering the service” (Dabholkar, 1999,p.484). Similarly, participation activities for value co-creation in anexhibition are referred to as the degree to which an exhibitor partici-pates in the process of value co-creation in producing and delivering theexhibition. Four common participation activities in value co-creationhave been identified by different researchers (see Table 1) that mayoccur during the production and delivery of an exhibition. These fourparticipation activities are: ‘Information Seeking’, ‘InformationSharing’, ‘Responsibility’, and ‘Situational Awareness’.Firms seek information from other stakeholders to gain a deeperunderstanding of their customers and market trends (Johanna et al.,2012). Furthermore, information seeking assists firms in involvingthemselves in the value co-creation process, thus improving their per-ceived performance (Saarijärvi et al., 2013). Therefore, informationseeking is regarded as a value co-creation activity performed by ex-hibitors in exhibitions.Information sharing facilitates access and dialogue between the firmand customers (Hatch and Schultz, 2010; Maglio and Spohrer, 2008).As additional customers share their information with the firm, the morelikely the firm will benefit from the value co-creation process and hencedeliver a satisfying outcome(Aarikka-Stenroos and Jaakkola, 2012).Therefore, information sharing is another crucial component of theparticipation activities of value co-creation in exhibitions.Participation concerns what might be described as a responsiblebehavior, so customers conform to the roles and duties expected ofthem by the service provider during the consumption process (Ennewand Binks, 1999). A customer with a high level of responsibility is re-garded as a ‘partial employee’ and assists the firm in service delivery(Yen et al., 2004). Therefore, responsibility should be a value co-crea-tion activity in exhibitions, because exhibitors should assume respon-sibility for their participation in an exhibition,Situational awareness is one’s perception and understanding of thedynamic environment (Wright et al., 2004). It helps to establish what“knowing what is going on” entails for projecting future situations(Endsley and Garland, 2000). Being aware of situations in exhibitions,exhibitors can proactively improve the value of services. Therefore,situational awareness is a value co-creation activity in exhibitions.2.2.2. Partnership activitiesA working definition of a partnership is “a collaborative relationshipbetween entities to work toward shared objectives through a mutuallyagreed division of labour” (World Bank, 1998, p.5). In this study,partnership activities refer to the behaviors an exhibitor performs as apartner in the value co-creation process during the production anddelivery of an exhibition. The partnership activities of value co-creationin exhibitions that are commonly quoted by many researchers (seeTable 1) include ‘Engagement’, ‘Knowledge Transfer’, ‘Resolving Con-flict’, and ‘Commitment’.Customer engagement is a psychological state (Brodie et al., 2011)that affects value co-creation by virtue of customers’ diverse resourcecontributions toward the focal firm and other stakeholders (Jaakkolaand Alexander, 2014; Sashi, 2012). Therefore, engagement is addressedas a type of partnership activity in which customers behave beyond asimple transaction and may influence the firm’s performance (Brodieet al., 2013; Verhoef et al., 2010). Engagement should be a value co-creation activity in exhibitions because exhibitors contribute varioustypes of resources such as time and ideas in exhibitions.Knowledge transfer is referred to the process through which oneunit is affected by the experience of another (Argote and Ingram, 2000).In a partnering network, knowledge is transferred through actor-to-actor interaction. Knowledge transfer is a driver of innovation andproductivity, and it is particularly important in terms of competitive-ness (Shaw and Williams, 2009). For an exhibition, knowledge transferfrom exhibitors to the organizer may occur in the process of producingand delivering an exhibition.Resolving conflict is referred to as the degree to which customersare willing to working actively with the firm to solve a joint problemFig. 2. Impact-asymmetry analysis.J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131120
(Jeon et al., 2016; Mohr and Spekman, 1994). Conflicts are often in-evitable and unexpected, and they may cause a negative impact if theyare not managed appropriately (De Dreu and Weingart, 2003). So it isnecessary for a partner to understand the effects of conflicts and to beable to work closely with other partners to solve the conflicts (Mele,2011). An exhibitor as a partner in an exhibition should be ready towork with the organizer to resolve any conflicts.Many studies have addressed the importance of commitment in theprocess of value co-creation in partnership activities (Blythe, 1999;Bowen and Shoemaker, 1998; Randall et al., 2011). For example,Bowen and Shoemaker (1998) argued that commitment is a belief thatpartners should be willing to work to maintain the relationship.Gummesson and Mele (2010) argued that value co-creation is a time-based process that is enabled by actor-to-actor commitment.3. Research method3.1. Research designThe objective of this study is to assess the symmetric and asym-metric effects of value co-creation activities performed by exhibitorswhich affect their satisfaction and dissatisfaction with exhibitions. Forhelping readers to grasp the idea of the study, a diagram of the researchflow of this study is shown in Fig. 3.3.2. Measurement scaleThis study attempts to assess the symmetric and asymmetric effectsof value co-creation activities performed by exhibitors at exhibitions.To achieve this research objective, we must develop a value co-creationmeasurement scale to measure exhibitors’ co-creation processes be-cause no specific value co-creation measurement models were dis-covered during the literature review. Based on the literature review,two types of value co-creation activities (participation and partnership)composed of eight value co-creation activities are identified, as shownin Table 1. The first focus group meeting with eleven exhibitors andindustry experts was conducted to create the initial set of measurableitems based on their own conceptual definitions. The initial set ofmeasurement items consisted of five to eight measurable items for eachvalue co-creation activity. The second focus group meeting, includingfive members from the first focus group and five new members (ex-hibitors), was conducted to revise, combine, rate, sort, and finalize themeasurement items for each activity. During the second focus groupmeeting, group members reviewed the definitions of the value co-creation activities and their measurement items and rated the mea-surement items for each activity based on their inter-judge reliabilityand criterion-related validity. Only the most representative items wereselected for each activity to shorten the survey while not disrupting theoriginal features of the activity. Then, these selected items wereproofread to ensure they were understandable. The average length ofthe two focus group meetings was approximately 2 h. Based on theresults of the second focus group meeting, 31 measurement items foreight activities were obtained to reflect exhibitors’ potential behaviorsduring value co-creation in exhibitions (as shown in Table 3).Since exhibitors intend to collect different types of information fromother stakeholders such as attendees, the measurable items for in-formation seeking are based on this intention, such as “We are lookingfor market information in this exhibition.” Additionally, exhibitors alsointend to share information with other stakeholders, so the measurableitems for information sharing reflect this intention, such as “We wouldlike to share market information with attendees, the exhibition orga-nizer, and other exhibitors in this exhibition.” In an exhibition, ex-hibitors are responsible for all the tasks in their booth. Therefore, themeasurable items for responsibility are related to tasks in their booth,such as “We are responsible for securing our booth in the exhibition.”Exhibitors must be aware of what is occurring in the exhibition, so “Inthis exhibition, we would like to recognize the situation of the exhibi-tion” will be asked.In an exhibition, exhibitors must engage with different tasks. Theywould like to provide feedback for improving the quality of the ex-hibition. Therefore, the measurable items for engagement place em-phasis on providing information for improving the quality of the ex-hibition, such as “We would like to provide feedback on the design ofthe exhibition.” As business partners, exhibitors are willing to sharetheir knowledge concerning exhibition implementation with the orga-nizer. So, to measure the knowledge transfer, the question “We proac-tively share our best practices with the exhibition organizer” will beasked. When participating in an exhibition, exhibitors may haveTable 1The attributes of value co-creation in recent studies of service sectors.Activity Attribute ReferenceParticipation Information Seeking Chang and Caneday (2011); Énalan and Soteriades (2012); Ho et al. (2012); Kastenholz et al. (2012); Morosan and DeFranco (2016); Parkand Oh (2012); Yi and Gong (2013)Information Sharing Aarikka-Stenroos and Jaakkola (2012); Hatch and Schultz (2010); Haugland et al. (2011); Ho et al. (2012); Yi and Gong (2013)Responsibility Ennew and Binks (1999); Grimwood et al. (2015); Yen et al. (2004); Weaver (2014); Yi and Gong (2013)Situational Awareness Endsley and Garland (2000); Jin et al. (2012); Lee et al. (2015); Wright et al. (2004)Partnership Engagement Brodie et al. (2011, 2013); Chathoth et al. (2014); Jaakkola and Alexander (2014); Sashi (2012); So et al. (2014)Knowledge Transfer Argote and Ingram (2000); Carlisle et al. (2013); Morosan and DeFranco (2016); Shaw and Williams (2009); Weidenfeld et al. (2016);Weidenfeld et al. (2010); Williams and Shaw (2011)Resolving Conflict De Dreu and Weingart (2003); Mele (2011); Mohr and Spekman (1994); Yang et al. (2013)Commitment Blythe (1999); Bowen and Shoemaker (1998); Grissemann and Stokburger-Sauer (2012); Gummesson and Mele (2010); Lai (2015b);Randall et al. (2011)Fig. 3. Research flow of the study.J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131121
conflicts with the organizer. Exhibitors must participate in problem-solving with the organizer, so the measurable items for resolving con-flict reflect exhibitors’ attitudes towards conflict resolution, such as“When there is a conflict, we can smoothly overcome the problem withthe exhibition organizer.” Exhibitors as business partners require acommitment of cooperation with the organizer. The measurable itemsof commitment refer to the exhibitors’ feeling of commitment towardsthe organizer, such as “We felt attached to this exhibition organizer.”In this study, the symmetric and asymmetric effects of value co-creation activities are computed by measuring the impacts of eightvalue co-creation activities on the overall satisfaction of the value co-creation performance. The overall satisfaction is measured by threeitems extended from Lai (2015a) as a means to measure the level ofexhibitor satisfaction directly linked to the performance of the eightvalue co-creation activities in the exhibition, such as “We are fully sa-tisfied with the value co-creation performance in this exhibition.”3.3. Questionnaire design and data collectionThe questionnaire was composed of three sections. The first sectionwas a screening question to ask the respondents whether they feltcomfortable in representing their company in completing the ques-tionnaire. Only the respondents who answered “yes” would be invitedto complete the questionnaire. The second section asked the re-spondents to rate 34 questions for the eight value co-creation activitiesand overall satisfaction on a 7-point Likert scale, ranging from1= strongly disagree to 7= strongly agree. The final section includedquestions for demographic profiles, including the type of exhibition,country/region, company size, the number of exhibitions they partici-pated in per year, personal working experience in exhibitions, companyexperience in joining exhibitions, and personal position. The ques-tionnaire had a bilingual design; it was designed originally in Englishand then translated into Chinese, and it was proofread by two profes-sional translators.Four well-trained research assistants surveyed all of the exhibitorsin four differently sized exhibitions in Macao between July and August2016. The respondents could choose to answer the questions in eitherEnglish or Chinese. A total of 500 questionnaires were collected, but 63were found to be unusable because respondents did not complete thequestionnaires or gave the same rating for all of the questions. Finally,Fig. 4. The results of PLS analysis for participation activities.J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131122
437 questionnaires were valid for data analysis. Table A1 of theAppendix A shows the detailed background information of the re-sponding exhibitors.3.4. Enhanced impact-asymmetry analysisIn this study, there are two dimensions and each dimension consistsof four attributes. The regression equation for each dimension is asfollows:∑ ∑= + + +OS Constant RI RD PI PD errori i i i (6)where OS=overall satisfaction, RIi=reward index for attribute i,PIi=penalty index for attribute i, RDi=reward dummy for attribute i,PDi=penalty dummy for attribute iSince the measurable items of each value co-creation activity in thisstudy are not interchangeable (see Table 3), the proposed measurementscale is a formative measurement model. As recommended by Hair et al.(2017), PLS will be employed to compute the coefficients of the rewardand penalty indices for the value co-creation activities because PLS caneasily handle formative measurement models.By using Eqs. (2) through (5), the values of RIOS, SGP, DGP, and IAfor each value co-creation activity can be calculated. According toMikulic and Prebezac (2011) extant impact-asymmetry analysis, thereare three levels of impact on overall satisfaction and five categories offactor structure (as shown in Fig. 2), so each value co-creation activitywill fall into one of the fifteen quadrants. A corresponding strategicaction is recommended for each quadrant, as discussed in the followingsection.3.5. Strategic actionsThe strategic actions for this study are extended from the IPAstrategic actions and other impact-asymmetry analysis studies oftourism industries (Albayrak, 2015; Albayrak and Caber, 2015; Back,2012; Kano et al., 1984; Martilla and James, 1977). Firstly, dissatisfiersand frustrators are fundamental requirements that must be fulfilled.Their absence will make customers dissatisfied, or even frustrated, sofor the high- and medium-impact dissatisfiers and frustrators, the firmshould ‘maintain’ existing performance at a certain level to avoid cus-tomer dissatisfaction, but exceeding the requirement will not increasecustomer satisfaction. However, for the low-impact dissatisfiers andfrustrators, a ‘discard’ action is recommended as they have a low impacton customer dissatisfaction. These factors are seen as unimportant, sothe firm can possibly reallocate or redirect its resources to other im-portant factors as needed. ‘Discard’ means the task/service is no longerFig. 5. The results of PLS analysis for partnership activities.J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131123
desirable; therefore, the firm does not need to perform any action.Secondly, in the categories of the satisfiers and delighters, the cus-tomers may not expect but it makes them feel satisfied or even de-lighted if the firm performs well. Thus, for the medium- and high-im-pact satisfiers and delighters, an ‘aggressive’ strategic action issuggested, meaning the firm should put additional effort into theseactivities and attempt to offer additional services for these items toincrease customer satisfaction. However, for the low-impact satisfiersand delighters, because customers can be content without these re-quirements and they have a low impact, it is not necessary for the firmto expend any effort; therefore, a ‘discard’ strategy is recommended.Finally, hybrids show approximately symmetric impacts on overallsatisfaction. For medium- and high-impact hybrids, the values of thereward and penalty indices are high, so the firm should take ‘aggressive’actions to enhance customer satisfaction. For low-impact hybrids, theeffects of the reward and penalty indices on satisfaction and dis-satisfaction are non-significant and their values are low, so the firm mayemploy a ‘low priority’ strategy as the firm’s resources are limited. Sincethere is no significant incentive for their improvement, the firm canfocus less attention on these items and maintain its efforts on medium-and high-impact hybrid factors. However, if the firm has sufficient re-sources, it can expend appropriate efforts to increase customer sa-tisfaction on the low-impact hybrid factors.4. Findings4.1. Exploratory factor analysisExploratory factor analysis using SPSS version 16.0 was used toidentify the underlying components. For the participation dimension,the initial value of the Kaiser-Meyer-Olkin (KMO) test is 0.899; there-fore, the data was found to be significantly correlated and suitable forfactor analysis (Hair et al., 2010). A principal component analysis witha varimax rotation was performed. Items that had communality below0.5 or loaded highly on more than one component were excluded(Bernstein, 2012). After two cycles of reducing the insignificant attri-butes, two items were removed and 13 items were retained for fourcomponents. For the partnership dimension, the initial value of theKMO test is 0.933. After a cycle of reducing the insignificant attributes,one item was removed and 15 items were retained for four components.The final values of the KMO test are 0.880 and 0.931 for the partici-pation and partnership dimensions, respectively. The total varianceexplained for two dimensions are shown in Table A2 of the Appendix A.The rotated factor matrixes for two dimensions are shown in Table A3of the Appendix A.4.2. Construct reliability and validityFor further evidence of the construct validity of the new measure-ment scale as recommended by Lai and Hitchcock (2015), a con-firmatory factor analysis (CFA) was executed as part of the PLS-SEM run(Lowry and Gaskin, 2014) by using the SmartPLS 2.0.M3 (Ringle et al.,2005) software program. Table 3 shows the mean, standard deviation,and PLS loading of each measurable item. The factor loading of eachmeasurable item is higher than the recommended 0.50. As shown inTable 3, the values of Cronbach’s alpha of all constructs are above therecommended value of 0.70 for meeting acceptable reliability, theFig. 6. The results of impact-asymmetry analysis.Table 2The proposed strategic actions for impact-asymmetric analysis.Factor Low-impact Medium-impact High-impactDelighter Discard Aggressive Highly AggressiveSatisfier Discard Aggressive AggressiveHybrid Low priority Aggressive Highly AggressiveDissatisfier Discard Maintain MaintainFrustrator Discard Maintain Strongly MaintainJ.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131124
values of the composite reliability (CR) of all constructs exceed therecommended value of 0.7 for ensuring adequate construct reliability,and the value of the average variance extracted (AVE) of each constructis higher than the recommended value of 0.50 for satisfying convergentvalidity (Hair et al., 2010). The square root of the construct’s AVE ex-ceeds its correlations with other constructs, as shown in Table 4. Thus,the above results provide supporting evidence of discriminant validityfor all constructs.4.3. Structure of value co-creation activitiesAn enhanced impact-asymmetry analysis was conducted as de-scribed in Section 3.4. The first step is the creation of two sets ofdummy variables. The grand mean of 28 measurable items is 5.566, sotwo values (5 and 6) were classified as the boundary between high- andTable 3Mean, standard deviation, and factor loading of measurable items (n=437).Measurable item Mean S.D. PLS loadingInformation Seeking (ISe) (Cronbach’s Alpha=0.881, AVE=0.808, CR=0.926)ISe1 We are looking for market information in this exhibition. 5.638 1.099 0.901ISe2 We are looking for product information in this exhibition. 5.682 1.082 0.922ISe3 We are looking for customer information in this exhibition. 5.755 1.059 0.872Information Sharing (ISh) (Cronbach’s Alpha=0.820, AVE=0.735, CR=0.893)ISh1 We would like to share market information with attendees, the exhibition organizer, and other exhibitors in this exhibition. 5.616 1.042 0.892ISh2 We would like to share product information with attendees, the exhibition organizer, and other exhibitors in this exhibition. 5.620 0.999 0.869ISh3 We would like to share customer information with attendees, the exhibition organizer, and other exhibitors in this exhibition. 5.382 1.224 0.809Responsibility (Res) (Cronbach’s Alpha= 0.844, AVE=0.762, CR=0.906)Res1 We are responsible for delivering our booth in the exhibition. 5.753 1.031 0.871Res2 We are responsible for maintaining our booth in the exhibition. 5.739 1.080 0.900Res3 We are responsible for securing our booth in the exhibition. 5.707 1.048 0.847We are responsible for serving the attendees at our booth in the exhibition.* 5.973 0.997Situational Awareness (Sit) (Cronbach’s Alpha= 0.846, AVE=0.686, CR=0.897)Sit1 In this exhibition, we would like to anticipate the needs of the exhibition. 5.245 1.101 0.788Sit2 In this exhibition, we would like to recognize the situation of the exhibition. 5.357 1.039 0.880Sit3 In this exhibition, we would like to understand the condition of the exhibition. 5.435 1.020 0.850Sit4 In this exhibition, we would like to deal with the situation of the exhibition. 5.481 1.013 0.791In this exhibition, we would like to adapt to current task demands efficiently.* 5.515 1.028Engagement (Eng) (Cronbach’s Alpha=0.857, AVE=0.700, CR=0.903)Eng1 We would like to provide objective information to the exhibition organizer. 5.579 1.003 0.800Eng2 We would like to provide feedback on the design of the exhibition. 5.529 1.017 0.852Eng3 We would like to assist the exhibition organizer to promote the exhibition. 5.588 1.023 0.864Eng4 We would like to provide consultation on the matters about the exhibition. 5.529 1.017 0.827We would like to provide suggestions for improving the quality of the exhibition.* 5.643 1.003Knowledge Transfer (KTr) (Cronbach’s Alpha= 0.835, AVE=0.753, CR=0.901)KTr1 We actively share our knowledge concerning work with the exhibition organizer. 5.625 0.937 0.889KTr2 We proactively share our best practices with the exhibition organizer. 5.668 0.905 0.874KTr3 We interact with the exhibition organizer to share what we learned concerning the exhibition 5.524 0.969 0.839Resolving Conflict (RCo) (Cronbach’s Alpha= 0.816, AVE=0.731, CR=0.891)RCo1 When there is a conflict, we are willing to engage in joint problem solving with the exhibition organizer. 5.568 0.895 0.845RCo2 When there is a conflict, we can smoothly overcome the problem with the exhibition organizer. 5.533 0.902 0.883RCo3 When there is a conflict, we can research a mutually satisfactory solution with the exhibition organizer. 5.529 0.892 0.838Commitment (Com) Adapted from Lai (2015a, 2015b) (Cronbach’s Alpha= 0.888, AVE=0.692, CR=0.918)Com1 We have always felt at ease with the exhibition organizer. 5.526 0.927 0.808Com2 This exhibition organizer has always been courteous and friendly. 5.611 0.941 0.806Com3 We felt very loyal to this exhibition organizer. 5.561 0.938 0.865Com4 We felt a sense of identification with this exhibition organizer. 5.542 0.937 0.866Com5 We felt attached to this exhibition organizer. 5.533 0.994 0.811Grand mean of 28 measurable items 5.566Overall Satisfaction (OS) Adapted from Lai (2015a, 2015b) (Cronbach’s Alpha= 0.846, AVE=0.765, CR=0.907)OS1 We are fully satisfied with the value co-creation performance in this exhibition. 5.577 0.937 0.862OS2 The value co-creation performance in this exhibition met our expectations. 5.535 0.879 0.878OS3 In this exhibition, we are satisfied with its value co-creation performance compared to other exhibitions. 5.618 0.915 0.883Note: AVE − Average Variance Extracted. CR − Composite Reliability, S.D. − Standard Deviation, * Removed measurable item.Table 4Reliability, Validity, Correlations and Square Roots of AVEs.ISe ISh Res Sit Eng KTr RCo Com OSISe 0.899ISh 0.557 0.857Res 0.490 0.526 0.873Sit 0.375 0.468 0.447 0.828Eng 0.460 0.556 0.581 0.585 0.837KTr 0.348 0.419 0.448 0.442 0.549 0.868RCo 0.406 0.392 0.477 0.458 0.517 0.509 0.855Com 0.458 0.463 0.513 0.557 0.581 0.561 0.611 0.832OS 0.372 0.412 0.420 0.487 0.510 0.607 0.549 0.684 0.875Remark: 1. ISe − Information Seeking, ISh − Information Sharing, Res − Responsibility,Sit − Situational Awareness, Eng − Engagement, KTr − Knowledge Transfer, RCo −Resolving Conflict, Com − Commitment, OS − Overall Satisfaction.2. Italic front − square-root of Average Variance Extracted (AVE).J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131125
low-performance levels. Thus, the value 7 was classified as high-per-formance level and the values 4 or less were classified as low-perfor-mance level. The reward dummy set to measure the impact of an ex-tremely high performance (rate= 7) was established as the PLS factorloading of the measurable item (as shown in Table 3) and other ratings(rate= 1 to 6) were set to “0”. The penalty dummy set to measure theimpact of an extremely low performance (rate= 4 or less) was estab-lished as the PLS factor loading of the measurable item and other rat-ings (rate= 5 to 7) were set to “0”. The setting of dummy values for thisstudy is shown in Table A4 of the Appendix A. A PLS regression wasthen performed to obtain the reward and penalty indices of each valueco-creation activity as defined in Eq. (6) on participation and partner-ship activities respectively. Figs. 4 and 5 show the results of the PLSanalysis with the setting of bootstrapping using 437 cases and 5000samples. Table 5 reports the calculated values of RIOS, SGP, DGP, andIA for each value co-creation activity by using Eqs. (2) through (5). Thevalues of RIOS and IA are used to determine the structure of each ac-tivity. The use of PLS factor loading for defining the dummy variablewill be discussed in Section 5.1.There are one delighter, one satisfier, two dissatisfiers, and fourhybrids. Engagement is a low-impact delighter (RIOSEng= 0.094,IAEng= 0.809) and information sharing is a medium-impact satisfier(RIOSISh= 0.148, IAISh= 0.581). Information seeking and resolvingconflict are medium-impact dissatisfiers (RIOSISe= 0.172,IAISe=−0.233; RIOSRCo= 0.144, IARCo=−0.361). Situationalawareness, knowledge transfer, and commitment are high-impact hy-brids (RIOSSit = 0.395, IASit = 0.058; RIOSKTr= 0.341, IAKTr= 0.138;RIOSCom=0.540, IACom=0.007). Responsibility is a medium-impacthybrid (RIOSRes= 0.162, IARes=−0.185). Fig. 6 shows the graph ofthe impact-asymmetry analysis.5. Discussions and conclusion5.1. Theoretical contributionsThis research focuses on accessing the factor structure of value co-creation activities of exhibitors that affect their satisfaction and dis-satisfaction with exhibitions by using an enhanced impact-asymmetricanalysis. The results of this study show that different value co-creationactivities in participation and partnership dimensions of the value co-creation measurement model have symmetrical and asymmetrical re-lationships with exhibitors’ overall satisfaction and dissatisfaction withexhibitions.There are four primary theoretical contributions from this study.Firstly, this study develops a new value co-creation measurement scalethat encompasses two dimensions: participation and partnership, whichwork together to influence the degree of value co-creation inexhibitions. Specifically, in this study, four participation activities (in-formation seeking, information sharing, responsibility, and situationalawareness) and four partnership activities (engagement, knowledgetransfer, resolving conflict, and commitment) are identified. The ma-jority of the previous studies in service industries discuss how customerparticipation can create value in co-creation processes. For example,Dong et al., 2008 studied the effects of customer participation in co-created service recovery. A limited amount of literature explored howcustomers can be treated as partners for creating value in co-creationprocesses. This study demonstrates the existence of another type ofvalue co-creation activity and validates the measurable items for bothtypes of value co-creation processes. Although this study only verifiesthese value co-creation activities in the exhibition sector, the proposedmeasurable items can be extended for studying value co-creation inother contexts where partnering is an important part of business de-velopment. For example, the partnership is a key element of tourismbecause it involves the coordination and cooperation among manybusinesses to provide access, accommodation, food services, attrac-tions, shopping, and entertainments for satisfying visitor needs. Thepartnership is also playing an important role in retailing, the operatorsof shopping malls need to coordinate and cooperate with retailers toprovide co-creation value to the shoppers. Thus, this study contributes avalue co-creation measurement scale that researchers can employ infurther studies to explore the impacts of these co-creation activities inother service sectors.Secondly, this study enhances our knowledge of conducting theimpact-asymmetry analysis. The majority of studies on impact-asym-metry analysis use a single item to evaluate the effect of one type ofservice on satisfaction (Back, 2012; Mikulic and Prebezac, 2008, 2011).However, there is a lack of literature showing the measurement ofimpact-asymmetry analysis by using multiple items, especially by usinga formative measurement scale. As single-item measures do not allowfor adjustment of measurement error, and this generally decreases theirreliability and causes lower predictive validity, it is suggested that amultiple-item measure is an improved method to measure a construct(Hair et al., 2017). In this study, the PLS analysis is introduced to assessthe formative measurement model with multiple items to compute thecoefficients of reward and penalty indices for all eight of the value co-creation activities.The extant impact-asymmetry analysis methods only measure thethree-factor structure of a single item or a dimension of multiple re-flective items by setting the value of the dummy variable to “1”. Thisstudy suggests using the factor loading of an item as its dummy variablevalue instead of using a uniform value of ‘1′ because factor loadings offormative items are outer weights that determine each indicator’s re-lative contribution to the construct (Hair et al., 2017). Unlike reflectiveindicators which inter-correlations are high, different formativeTable 5Factor Structure of Co-creation Activities.Reward- index t-statistics Penalty- index t-statistics RIOS SGP DGP IA Factor category ActionParticipation activities (R-Square= 0.299)ISe 0.066 1.391 −0.106 2.303 0.172 0.384 −0.616 −0.233 Medium-impact Dissatisfier MaintainISh 0.117 2.742 −0.031 0.667 0.148 0.791 −0.209 0.581 Medium-impact Satisfier AggressiveRes 0.066 1.495 −0.096 1.944 0.162 0.407 −0.593 −0.185 Medium-impact Hybrid AggressiveSit 0.209 4.963 −0.186 4.170 0.395 0.529 −0.471 0.058 High-impact Hybrid Highly AggressivePartnership activities (R-Square= 0.529)Eng 0.085 2.222 −0.009 0.207 0.094 0.904 −0.096 0.809 Low-impact Delighter DiscardKTr 0.194 5.019 −0.147 2.890 0.341 0.569 −0.431 0.138 High-impact Hybrid Highly AggressiveRCo 0.046 1.503 −0.098 2.071 0.144 0.319 −0.681 −0.361 Medium-impact Dissatisfier MaintainCom 0.272 7.971 −0.268 5.859 0.540 0.504 −0.496 0.007 High-impact Hybrid Highly AggressiveRemark:.1. RIOS − Range of Impact on Overall Satisfaction, SGP − Satisfaction-Generating Potential, DGP − Dissatisfaction-Generating Potential, IA − Impact-Asymmetry.2. ISe− Information Seeking, ISh− Information Sharing, Res− Responsibility, Sit− Situational Awareness, Eng− Engagement, KTr− Knowledge Transfer, RCo− Resolving Conflict,Com − Commitment.J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131126
indicators of a construct have different contributions to the construct,such that different formative indicators of an exogenous variable havedifferent levels of influence on the endogenous variable. Therefore, theuse of factor loading of an item as its dummy variable value can providea better explanation of the relationships between exogenous variable(s)and the endogenous variable. This study provides a new method forresearchers to perform the impact-asymmetry analysis.Thirdly, previous studies of impact-asymmetry analysis do notprovide strategic actions similar to IPA, they only suggested that servicemanagers should make decisions concerning prioritizing the improve-ment of service attributes based on the results of the analysis (Mikulicand Prebezac, 2008, 2011). However, no specific strategic actions arespecified for managers to prevent customer’s dissatisfaction for dis-satisfiers and increase customer’s satisfaction for satisfiers. Thus, thishandicap prohibits the popularity of the application of impact-asym-metry analysis. To fill this gap, extended from the concept of IPA, thisstudy formulates four strategic actions (discard, low priority, maintain,and aggressive) for attributes in different factor categories. This studyprovides examples of the execution of these four strategic actions basedon the results of the impact-asymmetry analysis in the following sec-tions. By complementing these strategic actions, the impact-asymmetryanalysis becomes more integrated as a powerful tool and technique forstrategic management. Therefore, this study provides overarchingstrategic actions for academia to obtain a completed impact-asymmetryanalysis and for the industry to obtain strategic directions for enhancingcustomer satisfaction and preventing dissatisfaction. This study en-hances the strengths of the impact-asymmetry analysis and promotes itsapplication to academia and industry.Fourthly, this study integrates the concept of three-factor theoryinto the value co-creation theory. Galvagno and Dalli (2014) reviewed421 selected articles of value co-creation research published in businessand management journals and found only one study exploring thesymmetric and asymmetric impacts of various creative components onconsumers’ idea generation (Füller et al., 2012). Identifying the factorstructures of different value co-creation processes is important becausedifferent processes show different natures in determining the value co-creation performance. Classifying the natures of value co-creationprocesses assists in prioritizing the strategic actions for the effectivemanagement of those processes. Through the evaluation of the factorstructure of each value co-creation process, the nature of each value co-creation process can easily be understood. Only by adopting the three-factor theory can the characteristics of certain value co-creation activ-ities be explained and then appropriate actions can be taken. The fol-lowing paragraphs explain the asymmetric effects of four value co-creation activities and their corresponding strategic actions.In participation activities, ‘information seeking’ is a medium-impactdissatisfier and ‘information sharing’ is a medium-impact satisfier. Thisindicates that ‘information seeking’ is a requirement for exhibitors inthe exhibitions because every exhibitor expects to obtain market in-formation necessary to remain current in the industry. Hence, the ex-hibition organizers should ‘maintain’ their work to ensure the channelsof information seeking are smooth for the exhibitors. However, notevery exhibitor is willing to share information with others. Therefore,‘information sharing’ is something that not every exhibitor expects, butexhibitors would be satisfied if it occurs. This is because an exhibitorwill find the value co-creation performance of the exhibition is im-proved when exhibitors share information with others. Since ‘in-formation sharing’ involves not only an exhibitor but also the visitors,other exhibitors, and other stakeholders, the exhibition organizersshould take ‘aggressive’ actions to facilitate information sharing activ-ities. The exhibition organizers can develop channels such as seminarsand encourage exhibitors and other stakeholders to join the informationsharing activities.In partnership activities, ‘engagement’ is a low-impact delighter.Although exhibitors feel delighted if their engagement is fulfilled, theimpact is low. Exhibitor engagement is difficult to develop andmaintain, so the exhibition organizers can ‘discard’ it and allocate re-sources to other aspects. ‘Resolving conflict’ is a medium-impact dis-satisfier. It is reasonable and obvious that an exhibitor will feel un-happy if conflicts exist between it and the organizer. However, althoughconflicts are resolved, this exhibitor will not be happy as conflicts areinherently negative. Therefore, it is better for the organizers to ‘main-tain’ the work of resolving conflicts with the exhibitors.This study provides an alternative view that has been overlooked inprevious studies. The classification and prioritization of value co-crea-tion activities enable exhibition organizers to allocate their resourcesbased on their individual situation for effective management of ex-hibitions. The results of this study support the integration of the three-factor theory into the value co-creation theory. Therefore, this studycontributes to three-factor theory by showing its application in thevalue co-creation process.5.2. Implications in practiceIn exhibitions, the value co-creation activities between the exhibi-tion organizers and exhibitors can improve the performance of theexhibitions and increase exhibitors’ satisfaction. The results of thisstudy provide several suggestions for exhibition organizers in the pro-cess of value co-creation activities. Firstly, the results show that ‘si-tuational awareness’, ‘knowledge transfer’, and ‘commitment’ are high-impact hybrids and ‘responsibility’ is a medium-impact hybrid. Basedon the strategic actions shown in Table 2 the exhibition organizersshould take ‘aggregative’ actions to improve the value co-creationperformance to satisfy the exhibitors. To support ‘situational awareness’during an exhibition, the organizers should frequently detect andgather information such as the number of visitors and quickly updateexhibitors via online instant messaging (e.g., WhatsApp). To support‘knowledge transfer’, the organizers can arrange preparation andfollow-up meetings with exhibitors as channels for knowledge sharing.The organizers can also create online social networks where exhibitorsfrom different countries can share knowledge on the topics relevant tovalue co-creation. To support ‘commitment’, the organizers canstrengthen their relationship with committed exhibitors by offeringthem incentives for future exhibitions. The organizers should alsocommunicate with other exhibitors frequently by adopting customerrelationship management systems that assist in building their commit-ment toward the organizers. To support ‘responsibility’, the organizersshould clearly explain the duties and responsibilities of exhibitors ateach stage of an exhibition and provide necessary assistance for theexhibitors to complete their tasks, including serving the attendees attheir booths.‘Information seeking’ and ‘resolving conflict’ are in the category ofmedium-impact dissatisfiers. To avoid the dissatisfaction of the ex-hibitors, the exhibition organizers should maintain their efforts to un-derstand what information the exhibitors are seeking and facilitatethem obtaining the information. Although it is difficult to prevent aconflict between exhibitors and the organizer, if there is a conflict, theorganizer is responsible to resolve the issue. The organizer shouldclarify the issue and cooperate closely with exhibitors to develop op-tions for resolving the conflict.‘Information sharing’ is a medium-impact satisfier, so the organizerscan adopt aggressive actions including creating online platforms such asa discussion forum on the exhibition’s website for exhibitors and visi-tors to share market and product information. Furthermore, since theuse of social media has increased significantly, organizers can createFacebook pages for exhibitors and visitors to use to communicate.Interestingly, ‘engagement’ is the only activity in the low-impact cate-gory. Logically, the organizers do not need to do anything to supportthis factor. However, its RIOS value is not very small (0.094), so or-ganizers can implement inexpensive incentives such as certificates orawards for the exhibitors who have assisted the exhibition organizer inpromoting the exhibitions. The organizers can also encourageJ.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131127
exhibitors to provide feedback and consultation on matters concerningthe exhibitions.Value co-creation is not merely an obligation for the exhibitionorganizers. To have a win–win situation, exhibitors should be self-motivated to perform participation and partnership value co-creationactivities in exhibitions. Therefore, the organizers should generate avalue co-creation environment that facilitates and encourages the ex-hibitors to participate, and also establish a partnership structure thatenables exhibitors to share in value co-creation activities.5.3. Limitations and further studiesSeveral limitations are associated with this study. Because of thesmall size of the exhibitors and the limited geographic coverage of theexhibitions, the results may not be generalized to all countries in theexhibition industry. The researcher can employ this set of co-creationactivities in other countries to test the generalization of these value co-creation activities in the exhibition industry with a reasonably largesample size.There is a limitation in determining low- and high-performancelevels for generating dummy variables because the reward and penaltycoefficients may vary according to different low- and high-performancelevels which are employed for coding the dummy variables (Albayrakand Caber, 2013). Also, the possible non-linearity of the attribute im-pacts on overall satisfaction may be neglected. In this study, 4-or-lessand 7 were selected as the low- and high-performance levels respec-tively. Since the means of the 28 valid measurable items of value co-creation activities range from 5.245 to 5.755 and its grand mean is5.566, this setting should be appropriate since the data were normallydistributed and no major problems arose with the use of extreme valuesin this study, as discussed by Back (2012). Further investigation fordefining low- and high-performance levels is recommended for having aguideline in performing IAA in different Likert scales and different re-search settings.Although the value co-creation measurement scale developed in thisstudy is tailored for the exhibition industry, researchers can extend thisscale for other service sectors. Furthermore, this type of research can beperformed as a longitudinal study to evaluate the scores for each at-tribute, monitor the changing interests of the stakeholders, and developthe strategic actions for certain attributes accordingly.AcknowledgementThis research was supported by the Faculty Research Grant from theMacau University of Science and Technology (FRG-17-026-FHTM).Appendix ATable A1Background information of responding exhibitors (n=437).Frequency Percentage (%)Type of exhibition Public 219 50.1Business 64 14.6Mix 154 35.2Country/Region Hong Kong 97 22.2Macao 146 33.4China 133 30.4Europe 37 8.5America 6 1.4Others 18 4.1Company size 1–50 113 25.951–100 117 26.8101–150 70 16.0151–200 57 13.0201–250 23 5.3251–300 11 2.5Over 300 46 10.5No. of exhibitions per 1–3 210 48.1year 4–6 175 40.07–10 38 8.7Over 10 14 3.2Working experience in 1–3 years 120 27.5exhibitions (Personal) 4–6 years 147 33.67–10 years 93 21.3Over 10 years 77 17.6Experience in joining 1–3 years 115 26.3exhibitions (Company) 4–6 years 135 30.97–10 years 82 18.8Over 10 years 105 24.0Position Junior 47 10.8Middle 257 58.8Senior 133 30.4J.W.C. Wong, I.K.W. Lai International Journal of Hospitality Management 72 (2018) 118–131128
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