Improving logistics outsourcing performance through transactional and relational mechanisms under transaction uncertainties: Evidence from China

Abstract

Although previous studies have extensively examined the effectiveness of the two important control mechanisms in inter-firm relationship management – contracts and relational norms – their relative usefulness under different transaction constraints is still unclear. This study extends existing research on relationship management by exploring the effects of various transaction constraints on the use of contracts and relational norms. It also examines the effects of these two mechanisms on outsourcing performance. The analysis of data from 264 Chinese firms engaged in logistics outsourcing indicates that demand volatility has a negative effect on contracts but has no significant effect on relational norms. Supply volatility exerts an inverse U-shape effect on relational norms, but has no significant effect on contracts. When technology uncertainty prevails, firms are likely to increase their use of either contracts or relational norms. In contrast, when vendor contribution is highly unpredictable, firms will simultaneously reduce their use of contracts and relational norms. Furthermore, although relational norms enhance satisfaction more effectively than contracts, their positive effects on financial performance are not significantly different. These findings enrich relationship management research, especially with regard to control mode selection in situations of transaction uncertainty.

Introduction

The standardized delivery systems and changing technologies used in logistics, such as on-board computers, global positioning services (GPS), mobile applications, optimization logistics programs, and cloud computing, allow professional logistics service providers to perform logistic tasks more efficiently and at lower costs than firms can achieve with in-house systems (Logan, 2000). To better focus on core competencies, firms increasingly contract out their logistics operations to third-party logistics (3PL) providers. Through logistics outsourcing, firms can save an average of 11.8% on logistics costs, 24.6% on logistics assets, and 8.2% on inventory costs, while shortening their average lead time from 7.1 days to 3.9 days (Rui, 2008). For example, in Europe, 76% of large enterprises use 3PL, and 70% of them have more than one 3PL partner (Li, 2009). In the United States, 58% of companies use 3PL services, and 3PL accounts for 30% of the total logistics market (Rui, 2008).

As China establishes its status as the world׳s second largest economy and number one exporter, its public and private sector leaders have begun to view the logistics process as a key component of the nation׳s commerce (Chen et al., 2010). The Chinese government has realized the strategic importance of logistics, and has begun investing heavily in infrastructure, warehousing capability, and distribution facilities (Lau and Zhang, 2006). To accelerate the nation׳s economic development, the Chinese Ministry of Commerce acted in 2008 to remove the restriction on foreign investment in the logistics industry. Under this new policy, many state-owned, foreign-owned, Sino-foreign, and private logistics service providers have been established, and the Chinese logistics market has gradually emerged (Chen et al., 2010, Zhou et al., 2008). By the end of 2014, China׳s total logistics market volume had reached 213.5 trillion RMB (approximately 32.8 trillion USD), with a rate of growth of 7.9% (China Federation of Logistics & Purchasing, 2015).

However, the Chinese logistics industry still has many problems. The total expenditure on logistics is nearly 16.1% of China׳s GDP, which is more than twice that of many developed countries (e.g., in the United States it is about 8%) (China Federation of Logistics & Purchasing, 2015). In addition, the failure rate in outsourcing attempts is relatively high. The untraceability of vendor behavior and difficulty in evaluating vendor competence are considered the two most prominent reasons for these failures (Langley et al., 2006, Tsai et al., 2012). Some large domestic enterprises are taking steps to address these problems. For instance, JD.com, the largest e-retailer in China, has abandoned external logistics and invested heavily in building its own logistics system. After encountering difficulties in controlling the behavior of 3PL providers, JD.com grew dissatisfied with external logistics services, and decided to guarantee its own logistics service quality. Alibaba, China׳s largest B2B e-commerce platform, plans to invest 300 billion RMB (approximately 49 billion USD) over the next five years (from March 2013 to 2018) to build its own online logistics service platform – CAINIAO Logistics. This project aims to increase the traceability of logistics services by converting tracking activities from offline to online.

Chen et al. (2010) indicates that the high costs and high failure rates of the logistics industry can be blamed on the improper management of outsourcing relationships. However, there have been few studies of the management of client–vendor relations in logistics outsourcing (e.g., Tian et al., 2007). To date, most studies in this area have been focused on information system (IS) outsourcing (e.g., Heiskanen et al., 2008; Li et al., 2010; Rustagi et al., 2008; Straub et al., 2009; Tiwana and Keil, 2007). Typically, IS outsourcing relationships are examples of offshore outsourcing. The vendor firms are often located far away from the client firms, due to the cost advantages of operating in places remote from the clients’ business centers, and the resulting communication and coordination difficulties make it hard for client firms to prescribe and monitor vendor behavior (Carmel, 1999). Most studies of these issues have compared the options of process or outcome controls, which are distinguished mainly by the timing of the intervention¹ (e.g., Choudhury and Sabherwal, 2003; Gopal and Gosain, 2010; Tiwana, 2008). However, restricting the analysis of logistics control to studies of the timing of intervention is too simplistic. Different control structures are required for different types of relationships and different kinds of environments. The underlying mechanisms that influence relationship outcomes and the effectiveness of various control methods differ greatly from one situation to another. Better understanding of the control outcomes of various structures and forms will enable firms to choose the best control mechanisms. Such research can also provide firms with methods to evaluate the effectiveness of various logistics control practices.

In terms of structure and form, inter-organizational relationship control involves both transactional and relational mechanisms (Jap and Anderson, 2003, Liu et al., 2009, Poppo and Zenger, 2002). A wealth of research on inter-firm relationship management has already investigated the effectiveness of both transactional and relational mechanisms for enhancing exchange performance (Joshi, 2009, Tiwana and Keil, 2007), improving satisfaction (Gençtürk and Aulakh, 2007), accelerating knowledge acquisition and innovation (Wang et al., 2011, Li et al., 2010), and curbing opportunism (Cavusgil et al., 2004, Heide et al., 2007). The findings of these studies suggest that participating firms should use multiple mechanisms to manage their exchange relationships (Liu et al., 2009). However, these studies have focused mainly on the consequences of control mechanisms. The issue of how these mechanisms are influenced by transaction attributes appears to have received inadequate attention. Addressing this issue is important, as control is a strategic response to the specific attributes of a transaction. The characteristics of a transaction are functions of its context or environment (Jaworski, 1988). Moreover, the options for control methods are not pre-fixed. The type and extent of control is largely determined by the focal firm׳s characteristics, risk preferences, and performance expectations. These factors are also affected by transaction attributes. A mismatch between the mode of control and a firm׳s unique context is likely to cause organizational decline (Ouchi, 1979). Although some scholars have considered the effects of transaction attributes in their control studies, the factors are generally treated as moderators rather than antecedents (e.g., Cavusgil et al., 2004; Gençtürk and Aulakh, 2007; Zhou and Poppo, 2010).

To fill these gaps, this study investigates the effects of transaction uncertainty on both transactional and relational mechanisms, and then examines how these factors influence outsourcing performance in the Chinese logistics market. This study contributes to the literature on control and inter-organizational relationship management by identifying how transaction uncertainty influences the modes of control used and the quality of outsourcing performance. The study׳s findings also enhance outsourcing performance by helping managers to choose the appropriate control for different transaction constraints.