Introduction An important decision that a manufacturer has to make in distributing a product to customers is the degree of forward channel integration (Aulakh & Kotabe, 1997; Coughlan et al., 2001; John & Weitz, 1988). Transaction cost economics (TCE) developed by Williamson (1975, 1985, 1986, 1999) has been one of the leading theoretical frameworks used to explain the channel integration decision (Frazier, 1999; Watson et al., 2015). TCE is generally a theory for explaining the choice of an efficient governance structure in transactions and includes asset specificity, uncertainty, and frequency as its explanatory variables. According to Williamson (1985, 1986, 1999), much of the explanatory power of TCE is driven by asset specificity. TCE-based channel integration studies argue that as asset specificity increases, firms are expected to increase the degree of channel integration. This study proposes to extend existing research in four important ways. First, existing studies have not examined individual dimensions of asset specificity. This study examines two important dimensions discussed by TCE: human asset specificity and physical asset specificity. Second, existing studies have tended to measure asset specificity in a particular way (i.e., with a particular set of questionnaire items). This study examines the robustness of the estimated asset specificity-integration relationship to alternative measures of asset specificity. Third, existing studies have focused on firms in one country such as the United States, Canada, or Germany. This study empirically examines the roles and relative importance of human and physical asset specificity in channel integration in two countries with different cultures, the United States and Japan. Fourth, existing studies have not investigated the possibility of endogeneity between asset specificity and channel integration. This study tests whether asset specificity is endogenous in explaining channel integration through an instrumental variables and two-stage least squares (IV-2SLS) approach. Literature Review In the context of distribution channels, asset specificity refers to the extent to which durable, transaction-specific investments in human and/or physical assets are needed to distribute the product in question (John & Weitz, 1988; Klein et al., 1990; Shervani et al., 2007). Examples of such investments include (1) the time and effort employed to acquire the firm-specific, product-specific, and customer-specific knowledge needed for distribution activities, and (2) specialized physical equipment and facilities (e.g., warehouses, deliver vehicles, refrigeration equipment, demonstration facilities, and repair and service centers) (Anderson, 1985; Bello & Lohtia, 1995; Brettel et al., 2011a, 2011b; John & Weitz, 1988; Shervani et al., 2007; Williamson, 1985, 1986). According to TCE, when the assets needed to distribute a product are non-specific, the use of independent channels is a priori more efficient than the use of integrated channels based on the benefits of distribution specialists and competition in the market place (Anderson, 1985). Conversely, a high level of specific assets, whether human or physical, has important implications for the degree of channel integration. The primary consequence is to reduce a large number of relationships between a manufacturer and independent channel members to a small number of relationships, which may expose the transaction in question to opportunistic behavior. Because the unique productive value created by a high level of specific assets makes it costly to switch to a new relationship, the use of independent channels will not be effective as a safeguard against opportunism (John & Weitz, 1988; Shervani et al., 2007). Channel integration provides a safeguard against opportunism by permitting (1) the better monitoring and surveillance of integrated channels relative to independent channels, and (2) the reduction of profits from opportunistic behavior since employees in integrated channels do not ordinarily have claims to profit streams (John & Weitz, 1988). As a result, as asset specificity increases, manufacturers are expected to increase the degree of channel integration to exercise greater control over the channels (John & Weitz, 1988; Shervani et al., 2007). This leads to the following basic TCE hypothesis concerning asset specificity and channel integration: TCE hypothesis. Asset specificity will be positively related to the degree of channel integration. Existing studies of channel integration tend to provide support or partial support for the hypothesized positive relationship between asset specificity and channel integration. One limitation of key studies is that they have not fully explored the dimensions of asset specificity because they treat asset specificity as unidimensional or examine only one dimension of asset specificity. Specifically, Anderson and Schmittlein (1984), Anderson (1985), Anderson and Coughlan (1987), and Krafft et al. (2004) focus on human asset specificity. While John and Weitz (1988), Shervani et al. (2007), and Brettel et al. (2011a) consider both human and physical asset specificity in their theoretical discussions, their empirical analyses focus only on human asset specificity. Klein et al. (1990), Aulakh and Kotabe (1997), and Brettel et al. (2011a) use a single measure of asset specificity that contains distinct items measuring human and physical asset specificity. Importantly, none of these studies has examined the dimension of physical asset specificity while controlling for the impact of human asset specificity. These observations suggest that further research is needed that explicitly measures and evaluates the relative importance of human and physical asset specificity in the channel integration decision. Research Hypotheses Based on the above literature review, we seek to extend existing research by distinguishing between two types of asset specificity, human and physical asset specificity. As already explained, TCE and TCE-based channel integration studies argue that both human and physical asset specificity are positive drivers of the degree of channel integration. Thus, our research hypotheses are the following: Hypothesis 1. Human asset specificity will be positively related to the degree of channel integration. Hypothesis 2. Physical asset specificity will be positively related to the degree of channel integration. Research Methodology As shown in Table 1, previous empirical studies attempt to test the basic TCE hypothesis concerning asset specificity and channel integration using (1) a particular measure of asset specificity, (2) data from a single national survey of firms in the United States, Canada, or Germany, and (3) methods such as an ordinary least squares (OLS) regression analysis and a partial least squares structural equation modelling (PLS-SEM) approach. In contrast with these studies, we seek to test the above two hypotheses concerning two types of asset specificity and channel integration using (1) different measures of asset specificity, (2) data from parallel national surveys of firms in two countries with different cultures, the United States and Japan, and (3) the methods used in prior empirical analyses and an IV-2SLS approach, which is a widely accepted method for investigating the potential endogeneity problem of focal explanatory variables (Antonakis et al., 2010, 2014; Zaefarian et al., 2017). This research strategy is partly based on the guidelines for high-quality replication studies articulated by Bettis et al. (2016b). The aims are to assess the generalizability of important prior results using different survey data drawn from different research contexts and to assess the robustness of these results using different measures and methods, thereby providing important additional evidence that contributes to the establishment of repeatable cumulative knowledge (Bettis et al., 2016a, 2016b). We developed the survey questionnaire in several steps. Following John and Weitz (1988), Shervani et al. (2007), and Brettel et al. (2011b), the dependent variable, channel integration, was operationalized by the percentage of sales through direct channels. We measured the focal explanatory variable, asset specificity, in four ways: (1) a four-item scale of human asset specificity used by Shervani et al. (2007), (2) a four-item scale of physical asset specificity based on Bello and Lohtia (1995) and Klein et al. (1990), (3) a six-item scale of human and physical asset specificity used by Klein et al. (1990), and (4) a four-item scale of human and physical asset specificity used by Brettel et al. (2011a). We also included four control variables: environmental uncertainty, behavioral uncertainty, financial performance, and channel members’ capabilities. Based on existing studies, manufacturers of electronic and telecommunication, metal, and chemical products in industrial (business-to-business) markets were selected as the setting for the empirical test. The unit of analysis was the domestic channel integration decision made at a product-market level. Respondents were sales/marketing managers (or executives) knowledgeable about channel design and strategies. In the United States, a professional marketing research company administered the data collection. In Japan, respondents were surveyed by mail. In total, we obtained 235 usable responses from US managers and 279 responses from Japanese managers. Results and Conclusions Following similar studies (John & Weitz, 1988; Shervani et al., 2007), an OLS regression analysis was used to test the hypotheses. The results, shown in Table 1, exhibit significant explanatory power for each model. As expected, (1) human asset specificity exhibits significant positive relationships with the degree of channel integration in both the United States and Japan (Models 1 & 2). These findings support Hypothesis 1. Conversely, (2) physical asset specificity does not have the expected significant positive relationships with the degree of channel integration in both the United States and Japan (Models 1 & 3). These findings do not support Hypothesis 2. Also, (3) asset specificity (Klein et al., 1990) and (4) asset specificity (Brettel et al., 2011a), two composite measures of human and physical asset specificity, exhibit the expected significant coefficients (Models 4 & 5). Additionally, we conducted a similar analysis using a structural equation modelling approach. The results mirrored those of OLS regression, thus providing further support for it. To assess the problem of potential endogeneity between asset specificity and channel integration, we employed IV-2SLS. We used (1) the level of the product’s technical content and (2) the need for coordination between production and distribution activities as instruments for human/physical asset specificity. Our instruments were individually significant predictors of asset specificity and met the exclusion restriction. However, the endogeneity test revealed no evidence of endogeneity. Thus, asset specificity was treated as exogenous in the model. In summary, our preliminary results suggest that human asset specificity, not physical asset specificity, is relevant to the channel integration decision. This finding is significant in that TCE-based channel integration studies tend to measure only one type of asset specificity. We are currently conducting additional analyses to better understand the relationship between human and physical asset specificity, for example, (1) the effects of human and physical asset specificity on different kinds of direct distribution, and (2) a multiple equation model in which human asset specificity is a function of physical asset specificity and direct distribution is a function of both human and physical asset specificity. We believe that our results will have important implications for the ways in which managers approach the channel integration decision.

Omotenashi is the Japanese term for a conception of service hospitality rooted in the Japanese tea ceremony. This research explores the ways in which contemporary hospitality executives have drawn on the historical tradition of omotenashi in the tea ceremony, as well as older Japanese cultural and spiritual traditions underlying omotenashi, to re-envision encounters between service employees and customers. In high context cultures like Japan, information is widely shared, which reduces the amount of information that must be shared verbally. The nature of Japan‟s high-context culture is manifested in two important principles of the philosophy of the tea ceremony. One important principle is mutual understanding, which arise from the process of “consideration,” which involves “putting oneself in the position of others to anticipate their desires” (Surak, 2012, p. 51). A second important principle involves ritualized social interactions. As Kondo explained (1985), “… the Japanese tea ceremony is a highly ritualized version of the host/guest interaction, and a heightened expression of the emphasis on etiquette in Japanese culture in general.” He continues: “The theory is that mere good intentions are insufficient; one must know the proper form in order to express one‟s feelings of hospitality effectively (Kondo 1985, p. 288). The importance of ritualized behavior also emerges in the kata of Kendo and other Japanese martial arts, where the term kata refers to a sequence of stylized movements that are designed to cultivate “speed of movement, dynamic execution, and realistic character” (Kiyota, 2002, p. 24). Similarly, Zen discussions of secular work emphasize the value of ritualized behavior. According to Musimi (1990, p. 821), “Deeply ingrained in the minds of the Japanese people is the belief that „work‟ makes for moral culture, and man‟s character is formed through the process of working.” Arai (2006, p. 110) observed that domestic work also can be viewed as “ritualized [Zen] activity done in accord with wisdom and compassion.” We argue that current attempts to implement the spirit of omotenashi in employee training have emphasized the spiritual, attitudinal, and behavioral dimensions of omotenashi. The meaning of these dimensions reflect the ways in which executives understand and interpret the high-context nature of Japanese culture and Zen Buddhism on the Tea Ceremony and Japanese martial arts such as Kendo.

Existing studies of Japanese consumers have emphasized the importance of collectivism and risk aversion in Japanese culture. In this paper we examine the relationship between these constructs in new product adoption decisions that involve brand switching. We argue that, for Japanese consumers, the perceived emotional risk of adoption is related to (1) the degree to which a consumer identifies with the brand of his or her current product and (2) the perceived performance, financial, and social risks of switching to an alternative product. We further hypothesize that perceived social risk is positively related to brand identification, perceived performance risk, and perceived financial risk. Finally, we hypothesize that financial risk is positively related to performance risk. We test our hypotheses using data collected in Japan in June 2015. Questionnaire items were adapted from existing, well-validated scales. The Japanese version of the questionnaire was developed by using the standard double translation procedure. The Japanese version of the questionnaire was administered by a marketing research firm to a national panel of respondents stratified by age and gender. The resulting sample consisted of 518 iPad owners from across Japan, of whom approximately half were men. Within each gender category, approximately half of the respondents intended to purchase a new tablet within the next 12 months. Following established SEM procedures, we began by estimating a confirmatory factory analysis model, after which we estimated a structural equation model. In each case, the estimated model satisfied standard evaluation criteria. In general, our findings provide support for the hypothesized model. First, Perceived Performance Risk was positively related with Financial Risk, Social Risk, and Emotional Risk. Second, Financial Risk was positively related with Social Risk. Third, Social Risk was positively related with Emotional Risk. Fourth, Brand Identification was positively related with Social Risk and Emotional Risk. The one hypothesized linkage that was not supported was the relationship between Financial Risk and Emotional Risk. A comparison of coefficient magnitudes reveals several important findings. First, in the Social Risk equation, the coefficient of Performance Risk is significantly larger than the Brand Identification coefficient. Second, within the Emotional Risk equation, the coefficient of Performance Risk is significantly larger than the coefficients of Brand Identification and Financial Risk. Similarly, the coefficient of Social Risk is also significantly larger than the coefficients of Financial Risk and Social Risk.

In this paper we explore the process of value co-creation in two elite kaiseki restaurant companies in Japan. The authors first describe key themes that underlie the omotenashi of the tea ceremony. The authors then examine the ways in which these themes influence the service philosopy of Teiichi Yuki, the found of the Kitcho restaurant chain, and Rikifusa Satake, the president of the Minokichi restaurant chain. Based on these analyses, we argue that existing discussions of co-creation, which focus on the customer’s creation of value-in-use, should be extended to permit the analysis of usage experiences that involve multiple, simultaneous, interdependent value-in-processes. In particular, in the two companies examined by the authors, both the master and the customer experience value-in-use during the delivery of kaiseki cuisine. Moreover, given the importance of mutual consideration, the value-in-use experienced by each party is critically dependent on the value-in-use received by the other.