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Supply chain collaboration, inter-firm trust and logistics performance:

Evidence from the tourism sector

Pairach Piboonrungroj (pairach@piboonrungroj.com)

Logistics Systems Dynamics Group, Cardiff Business School,

Cardiff University, United Kingdom, and

Chiang Mai School of Economics, Chiang Mai University, Thailand

Stephen M. Disney

Logistics Systems Dynamics Group, Cardiff Business School,

Cardiff University, United Kingdom, and

Department of Administrative Sciences, Metropolitan College, Boston University, Boston, United States of America.

Abstract Whether supply chain collaboration and inter-firm trust has a positive impact on logistics performance is still a subject of debate in the literature. This ambiguity has raised concerns among academics and practitioners. Therefore, we empirically examine the impact of supply chain collaboration and inter-firm trust on logistics performance. We first explore a real tourism supply chain to specify main factors and propose hypotheses. We then statistically test the hypotheses using data from six cases and a survey of 109 firms. The results show that, by establishing joint activities with their partners, firms could significantly improve their performance. Keywords: Supply chain collaboration, inter-firm trust, logistics performance Introduction One of the most important tasks of a supply chain manager is to build and sustain relationships between partners in order to improve the performance of the whole supply chain (Spekman et al., 1998; Mentzer et al., 2001; Christopher, 2005, p.5). Collaboration between firms in the supply chain is often quoted as the key to build and manage such relationships (Robson et al., 2008; Ireland and Webb, 2007; Kwon and Suh; 2004). Even though many firms have succeeded in implementing collaborative activities and have enhanced their performance, others have struggled or failed to do so. The reason why some firms were successful and some firms were not has perplexed academics and practitioners. To understand this problem it is essential to understand the

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mechanism by which collaboration improves logistics performance. Hence, our research aims to understand how firms effectively implement supply chain collaborative activities.

In this paper, a short literature review on supply chain collaboration is first presented. This is followed by a statement of our research methodology. Empirical findings are then presented, followed by a discussion on the results of this research. Finally, we suggest some future research avenues. Literature review Supply chain collaboration Supply chain collaboration could be defined as at least two firms in the same supply chain working together to achieve their mutual goals (Mentzer et al., 2001; Simatupang and Sridharan, 2002). It is believed that supply chain collaboration could yield large benefits as it is an enabler of the seamless supply chain (Childerhouse et al., 2004). The seamless supply chain is a theoretical goal where there is no boundary between firms and the supply chain thinks and acts as one (Towill, 1997). There are several collaborative approaches in the supply chains that could be taken e.g., information sharing, incentive alignment and decision synchronisation (Spekman et al., 1998; Akintoye et al., 2000; Holweg and Pil, 2008).

The performance of the supply chain is also heavily reliant upon accurate and timely information (Mentzer et al., 2001; Holweg et al., 2005). Supply chain collaboration can masquerade itself as vendor managed inventory, continuous replenishment programmes or collaborative planning forecasting and replenishment amongst others (Barrat, 2004; Holweg et al., 2005). Cost and benefits of supply chain collaboration Firms could expect a better level of responsiveness and service level improvements from their supply-chain collaborative programmes (Barrat, 2004). Another benefit would be a reduction of supply chain costs such as the costs of inter-firm transactions, inventory and production. Furthermore, it was found that collaboration could also reduce gaming and rationing in supply chains. This is one of the main causes of bullwhip effect (Holweg et al., 2005). Moreover, there are also benefits that could only be obtained via sophisticated collaboration such as the elimination of bullwhip effect, inventory reduction, better transport capacity utilisation, and risk mitigation (Spekman et al., 1998).

Undertaking collaborative action incurs both direct and indirect costs (Simatupang and Sridharan, 2002). Information and communication technology such as Internet and software for integrating operating systems and sharing information along the supply chains is considered a direct cost. However, there are indirect costs such as labour costs and opportunity costs that firms usually do not immediately understand. Costs and benefits of supply chain collaboration may vary according to circumstances (Spekman et al., 1998). First, geographical dispersion and the location of the firm and its supply chain partners may affect the need for collaboration and the benefits that can be obtained. Collaboration between supply chain partners that are geographically separated from each other may produce less benefit than collaboration between local supply chain partners. Secondly, demand patterns, especially seasonality, could influence the proper type and level of inter-firm collaboration (Barrat, 2004).

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Research Methodology The tourism sector is chosen as the context of this research as it makes a significant contribution to the economy and has both product and service characteristics. Specifically, we considered the dyadic relationship between hotels and their suppliers and travel agents. We collected data from the tourism sector in Thailand due to its reputation as one of the world’s most desirable tourist destinations and data accessibility. Thailand was ranked 12th and 17th in the world in terms of number of international tourist arrivals and international tourist receipts respectively in 2009 (World Tourism Organization, 2011). In this study, we implemented a three-stage methodology (Figure 1).

Figure 1 – Our Research Approach

Stage 1 – An exploratory case study and focus group interviews In order to familiarise ourselves with current industry practice we conducted a case study (Meredith, 1998) to explore the research problem in depth (Yin, 2003). The case hotel was selected because of its data accessibility. We also conducted semi-structured interviews (Voss et al., 2002) with hotel managers to obtain insights on the nature and impact of collaboration between the hotel and its supply chain partners. Stage 2 – Multiple-case study In the second stage of our research, we investigate the impact of supply chain collaboration across different tourism supply chains. Six hotel supply chains were selected using theoretical sampling (Meredith, 1998), controlling the location and the management systems of the hotels.

Stage 3 – Nationwide Survey In a nationwide survey, data was collected from a (self-administrated) questionnaire survey of tourism practitioners in Thailand. To develop the questionnaire, we adapted measurement items from existing scales in the relevant literature (Churchill, 1979). These measurement scales were validated by 11 tourism practitioners and four academics. The contents of questionnaire were initially developed in English language and independently translated to Thai language later by two experts from a Tourism Business Association (TBA) and the Language Institute of Chiang Mai University in Thailand to ensure conceptual equivalence. Then questionnaires were printed and distributed in the Annual meeting of the TBA. The informant firms were asked to

Stage 1: A Case Study & Focus Group

Interviews

Conceptual Framework

Questionnaire Development Survey Stage 3: Multiple

Regression Analysis

Semi-structured Interviews

Providing hypotheses (Facilitation)

Aiding measurement (Facilitation)

Stage 2: Multiple-Case Study

Research Hypotheses

Findings

Follow-up Interview

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indicate their perception and opinion of a familiar partner to gain the most accuracy of the data (Sriram et al., 1992). A further survey of tourism firms in Thailand was also conducted by post using a self-administrated questionnaire. Respondents returned their completed questionnaire via a stamped addressed envelope provided. A list of companies in the tourism industry was obtained from a government agency and the tourism business association. Empirical findings 1 – Exploratory case study and focus group interviews In the first stage of our research, we conducted an exploratory study via a single case study (with hotel and their supply chain partners) and two focus groups (consisting of both practitioners and academics). In this stage we identified the main types of supply chain collaboration techniques used in the tourism sector and developed a conceptual framework for supply chain collaboration. An exploratory case study We explored this case using in-depth interviews with the Food and Beverage Manager, the Director of Sales, the Chef and Finance Manager. We also studied company documents including purchase orders, inventory data and the business plan. In this case study, we found that the hotel focused on its relationship with the main food and beverage suppliers and a travel agency. To do so, they shared important (but not confidential) information between suppliers such as sales and promotion activities of major beverages (for example, beer and wine) as well as occupancy rate and room rate (promotions) with the travel agents. By sharing this information, the hotel expected benefits from marketing (higher sales) and operational aspects (product replenishment and delivery). Investment in people or equipment may be needed from their long-term partners. We found that the hotel managers’ satisfaction with their partners has a significant influence of the performance in their logistics activities including both physical flows with suppliers e.g., foods/beverage order and delivery and also information flows with travel agencies e.g., room reservation/booking. Moreover, we found that suppliers and travel agents with high logistics performance collaborated with the hotel by regularly sharing and updating important information. They also undertook joint team work and planning as well as investing in specific equipment or special training to create mutual understanding among the supply chain partners. Such effort slowly builds inter-organisational trust, enabling smooth operation of their business. This case study highlighted the importance of human factors on the impact of collaborative activities by building trust between supply chain partners. Trust is important as it produces positive outcomes in terms of logistics performance and relationship satisfaction. Focus-group interviews We held two focus-groups. The first group consisted of academics in tourism management and economics in Thailand. The second group were practitioners in the tourism sectors e.g., managers of hotels, suppliers and travel agents. In each group, we asked questions related to the types of supply chain collaboration in tourism sector, the role of inter-firm trust and consequences of those collaborative activities. Our case study finding led to the conceptual framework shown in Figure 2.

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 Figure 2 – Our Conceptual Framework

Empirical findings 2 – Multiple-case Study To further validate our conceptual framework multiple cases were used to compare the differences between the different types of firms selected (Yin, 2003). Findings from this stage are used to propose detailed research hypotheses. Sample cases Six hotels were selected based on their management system and location in order to compare and contrast their supply chain relationship. We classified hotel’s management system into three categories i.e., international chain hotels, local (domestic) chain hotels and non-chain (independent) hotels. The results of cross-case comparison presented in the Table 1 are used to propose the hypotheses introduced in the next section.  

Table 1 – Cross-case comparisons Hotel A Hotel B Hotel C Hotel D Hotel E Hotel F

Management System

International chain

Local chain Non-chain International

chain Local chain Non-chain

Destination Island destination

Island destination

Island destination

Mainland destination

Mainland destination

Mainland destination

Location Beach Shopping area City centre Beach Suburb

/Riverside Shopping

area Shopping

area Supplier (Main product)

Carbonated drinks Poultry Alcohol

drinks Carbonated

drinks Poultry Alcohol drinks

Travel agent (Main tourists)

European, Australian

Australia, Thai

European, Thai European European,

Thai Thai, French

Collaborative Efforts

- Information sharing High Moderate Low High Moderate High

- Joint activities High High Moderate Low High High - Dedicated

investment High Moderate High High Moderate Moderate

Inter-firm Trust - Trust belief High High Moderate Moderate High High - Trust behaviour High Moderate Low Moderate Moderate High Logistics Performance

- Order High High Moderate Moderate High High - Delivery High High Moderate Moderate Moderate High - Forecasting High Moderate Low Low Moderate High Satisfaction

- On commitment High Moderate Moderate Moderate High High

- On performance High High Low Moderate Moderate High

Collaborative Mechanism

Collaborative Efforts Collaborative Outcomes

Relationship Satisfaction

Logistics Performance

Interaction

Effects

Inter-firm trust

Information Sharing

Joint Activities

Dedicated Investment

Main

Effects

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Research hypotheses and construct operationalisation According to the findings from our multiple-case study, there are three main factors in the supply chain relationship model. These were collaborative efforts, mechanisms and outcomes. We also found that such collaborative efforts, via the mechanism of trust building between supply chain partners influence both logistics performance and relationship satisfaction.

Main effects of collaborative efforts We considered three collaborative activities including information sharing, joint activities and dedicated investment. Information sharing is believed to create the understanding in the partnership that leads to the higher level of trust (Nyaga et al., 2009; Doney and Connon, 1997; Monczka et al., 1998; Kwon and Suh, 2004). Joint activities are argued to be the essence of collaboration. When firms closely work together, they tend to understand each other more and this creates trust among the parties. Our multiple-case study finding suggests that joint activities could give rise to the inter-partner trust in the supply chain. This concurs with Min et al. (2005), Jap and Ganesan (2000) and Nyaga et al. (2009). Thus we propose the following hypotheses,

H1: Information sharing will have a positive effect on trust. H2: Joint activities will have a positive effect on trust. H3: Dedicated investment will have a positive effect on trust.

Interaction effects of collaborative efforts

Considering the collective impacts of the collaborative activities, the findings from the multiple-case studies suggests that firms are likely to receive greater benefit from collaboration when they implement various collaborative activities together. We propose to test that collaborative activities may have collective impacts with each other on inter-firm trust.

H4: Information sharing and joint activities have an interaction effect on trust. H5: Information sharing and dedicated investments have an interaction effect on trust. H6: Dedicated investments and joint activities have an interaction effect on trust.

Impacts of inter-firm trust Trust is claimed to be a critical factor in developing relationships in the supply chain (Christopher, 2005; Simatupang and Sridharan, 2002). Building inter-partner trust may produce better collaborative performance (Robson et al., 2008) and relationship satisfaction (Nyaga et al., 2009). In our multiple-case study, we found that supply chain partners who have higher levels of trust tend to have better logistics performance. Hence we propose the following hypothesis,

H7: Inter-firm trust will have a positive effect on logistics performance. H8: Inter-firm trust will have a positive effect on relationship satisfaction.

Impact of logistics performance on relationship satisfaction

Finally we would like to test whether better logistics performance leads to higher levels of relationship satisfaction between firms (Kwon and Suh, 2004; Nyaga et al., 2009). Hence, long-term relationships in supply chain could be established by an improvement in logistics performance driven by a higher level of trust.

H9: Logistics performance has a positive impact on relationship satisfaction.

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Empirical findings 3 - Survey and multiple regression models Confirmatory Factor Analysis (CFA) In the nationwide survey, we obtained 109 usable responses from hotels, suppliers and travel agents. All constructs have an acceptable internal reliability with a Cronbach’s alpha greater than 0.70. Loading scores (Jöreskog and Lawley, 1968) were all greater than 0.60 (Hair et al., 2010) but the last item, inter-firm trust (0.520), which still remained due to its conceptual importance. However, Confirmatory Factor Analysis (Jöreskog, 1969) of both measurement models show accepted fit indices (see Table 2).

Table 2 - Construct measures with reliability indices and factor loadings

Survey items Factor Loadings

CFA Model 1: Collaborative efforts (Chi-square/df =1.093, CFI=0.933, TLI=0.989, NFI=0.927, RMSEA=0.051, AIC=70.040)

Information sharing (α = 0.937) We inform this supplier/buyer in advance of changing needs. .926 It is expected that any information, which might help the other party, will be provided. .948 The parties are expected to keep each other informed about changes that may affect the other party. .883

Joint activities (α = 0.942) My firm and this supplier… … have a joint team. .921 … conduct joint planning to anticipate and resolve operational problems. .950 … make joint decisions about ways to improve overall cost efficiency. .887

Dedicated investments (α = 0.811) In building the relationship with my firm, this supplier… … has invested substantially in personnel. .847 … has provided proprietary expertise and/or technology. .829 … has dedicated significant investment. .632

CFA Model 2: Collaborative mechanism and outcomes (Chi-square/df =1.010, CFI=0.999, TLI=0.999, NFI=0.915, RMSEA=0.017, AIC=112.455)

Inter-firm trust (α =0.823) My firm can understand this supplier well. .812 This supplier is genuinely concerned that we succeed. .946 We trust this supplier keeps our best interests in mind. .667 This supplier/buyer considers our welfare as well as its own. .520

Satisfy with relationship (α = 0.900) My firm is satisfied with this relationship in terms of: - Coordination of activities. .826 - Participation in decision making. .809 - Level of commitment. .977

Logistics performance (α =0 .971) This relationship has … … improved our order processing accuracy. .949 … improved our on-time delivery. .858 … increased our forecast accuracy. .919 … improved our order accuracy in term of product types. .964 … improved our order accuracy in term of product quantity. .980

Note: α = Cronbach’s alpha Path analysis Results from our multiple regression models (Figure 3) show that only two collaborative activities (information sharing and dedicated investment) can build trust between supply chain partners on their own. However, it was found that collaborative teamwork (joint activities) enhances these collaborative activities. This result reveals that, in order to create a trust building environment in an inter-organisational setting, joint team effort acts as a multiplier on other collaborative activities.

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Note: *= p < 0.10, **p < 0.05, ***p < 0.01, **** p < 0.001

Figure 3: Result of Multiple Regression Models Considering the collective impacts of collaborative activities, we find statistically significant interaction effects only in those that include the joint activities (at p < 0.01) i.e., between joint activities and information sharing as well as between joint activities and dedicated investment. However, the main effect of the joint activities is not statistically significant on its own whilst those of information sharing and dedicated investment are (at p < 0.05). This finding reveals that even though joint the activities are not solely responsible for inter-firm trust, collectively they could enhance the impact of the other supply chain collaboration activities. However, since the coefficients of interaction effects of joint activities are positively significant with information sharing but negatively significant with dedicated investment, the higher level of joint activities could statistically enhance the benefit of information sharing on inter-firm trust but those of dedicated investment (see Figure 4).

High JA (= 1): Trust = 1.836*IS, High JA (= 1): Trust = -0.103*DI Moderate JA (=0): Trust = 0.766*IS, Moderate JA (=0): Trust = 0.767*DI Low JA (= -1): Trust = -0.545*IS, Low JA (= -1): Trust = 1.431*DI

Figure 4: Interaction effects of collaborative efforts

Inter-firm

Trust

Collaborative Outcomes

Interaction Effects Collaborative Efforts

Information Sharing (IS)

Dedicate Investment (DI)

Relationship Satisfaction

Logistics Performance

.767***

.511****

.766**

Joint Activities (JA) N.S.

.592****

IS x JA DI x JA

1 .070**** -0.664***

IS x DI

N.S.

.270*

R2=0.655 R2=0.350

R2=0.445

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Follow-up interviews Results from the multiple regression models were not only consistent with the multiple-case study but they also offered more insights. To further understand the consequences of the collaborative activities, we conducted follow-up interviews with practitioners and academics. The interviews confirmed that joint activities can enhance the creditability and comprehensibility of the information shared between supply chain partners because such activities can provide an opportunity to build inter-person trust and personal relationship between hotels and their supply chain partners. It was found that hotel managers are more likely to believe in data if they knew and trusted the person that gave them the information. However, even though joint activities could also enable knowledge transfer and mutual understanding between hotel employees and partners by allowing better utilisation of dedicated investment between partners (such as special equipment and policies), the impact is not significant. Thus, joint activities are a necessary when firms share their information with supply chain partners. Theoretical and managerial implications Theoretical implications This research advances the literature on inter-firm relationship management by proposing and empirically testing the interaction effects between different types of supply chain collaboration on inter-firm trust and logistics performance in both a product and service environment. This study also highlights the importance of interpersonal relationship in building trust between supply chain partners. Managerial implications This study also offers a clear insight for managers on how they can successfully implement supply chain collaboration activities in their organisations. We suggest that when firms already have collaborated with their partners by sharing information, they could significantly achieve a higher performance and satisfaction between their supply chain partners if they establish joint activities / teamwork with them. Conclusions and limitations Although many previous studies have found significant benefits from supply collaborations, managers still struggle to implement them successfully. Using a case study approach, we explored the issue of supply chain collaboration in the tourism sector in Thailand to gain an understanding of how firms could effectively gain benefit from such activities. We found that firms can the enhance benefits from supply chain collaboration if their employees work together with supply chain partners in a joint team. Using multiple regression models, our survey across the tourism sector in Thailand also confirmed these findings. The study also suggests that supply chain collaborations give rise to logistics performance via inter-firm trust between firms. Like any other research, this study also has limitations. As we only studied one industry, research findings may be varying in other industries. However, researchers may replicate our research in a different setting and compare the results with ours. Acknowledgement The authors are grateful to the Royal Thai Government through the Commission on Higher Education for financial support of Mr. Pairach Piboonrungroj’s study in Cardiff University under the program named Strategic Scholarships for Frontier Research.

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