Exploring Determinants Of Companies’ Collaboration Based In Morocco’s Free Zones

Abstract

This research is a response to the calls of many authors who urge testing conceptual frameworks, even the most elaborated, in an international context. It's also a continuation of the pioneering work on the collaboration of supply chain companies, with an original perspective on examining the determinants of the companies based in a developing country’s international free zones. The determinants of collaboration have been the subject of many conceptual and empirical developments without a consensus emerging from this research. To do so, four of the most recurrent mechanisms in western investigations that leads to a collaboration have been put to test: satisfaction, trust, commitment, and information sharing. The empirical study was conducted through a questionnaire sent to companies located in the two free zones of Tangier: Tangier Free Zone (TFZ) and Melloussa Free Zone (MFZ). Results show that the honesty and sincerity, the partners’ economic satisfaction are the main determinants of the logistic chain companies’ collaboration.

Keywords: Satisfactiontrustcommitmentinformation sharing and collaboration

Introduction

We argue that most research done to date on BtoB collaboration in the logistics chain has been conducted in developed countries and a lack of published research in developing countries has been noted. This severely limits the extrapolation of academic and managerial conclusions in these economies. Recognizing that developing countries have different characteristics from those of developed countries, Steenkamp (2005) calls for more research from an international perspective by integrating these developing economies where more than 80% of consumers live (Steenkamp & Burgess, 2006). The institutional contexts of developing economies hold socio-economic, demographic, cultural and regulatory gaps compared to theories assumptions developed in the Western world. In this perspective, they challenge the conventional understanding of constructs and their relationships. Conceptually, the external validity of established theories becomes less obvious.

The aim of this research is therefore, to contribute to the debate on the external validity of the models mobilized in the logistics chain. In other words, our ambition is to test a model of the determinants of collaboration, in the context of a developing country namely Morocco by choosing companies located in the free zones as a field of study.

Moreover, it should be emphasized that the supply chain’ B2B collaboration has been the subject of many conceptual and empirical developments. It has been addressed by researchers in sociology, psychology, marketing, management and supply chain management (Min et al., 2005). It has also been examined from the perspective of transaction cost theory (Nesheim, 2001; Barringer & Harrison, 2000), resource theory (Park, Mezias & Song, 2004; Verwaal & Hesselmans, 2004) institutional theory and resource dependency (Thomas & Rangannathan, 2005). These different theories have made collaboration a polysemic and multidimensional concept.

The diversity of approaches and the perspectives of analysis of the collaboration testify of this considerable interest and the craze of the researchers.

Several benefits result from collaboration. Collaborating companies will have greater success in achieving desired business outcomes such as cost reduction, quality improvement, better customer service and/or value improvement to customers and environmental uncertainty reduction (Zacharia, Nix, & Lush 2009; Kumar & Banerjee, 2014). In the same context, the partners join forces for the pooling of resources, a redefinition of roles distribution between partners, risks and/or costs sharing, the joint production of a product, the market knowledge sharing, developing a sustainable competitive advantage (Touboulic & Walker, 2015) to ultimately improve the overall performance of the company and the logistics chain (Sancha, Gimenez, & Sierra, 2016).

However, Zacharia, Nix, and Lush (2009) add that this collaboration between companies not only affects operational outcomes such as cost, quality or customer service, but also relational outcomes such as trust, credibility and relationship effectiveness.

Academically, a considerable increase in the number of published research has been reported. To ensure this, a search was launched in the Business Source Complete database with the keyword "collaboration in supply chain" from January 2000 to December 2015, the result shows that 1891 research were dedicated to the study of the collaboration in Supply Chain Management. In addition, in a globalized, complex, turbulent and competitive environment marked by the massive use of information and communication technologies, companies seek to establish close collaborative relationships with suppliers and customers. In this perspective, companies such as Hewlett-Packard, IBM, Dell, Procter and Gamble owe their competitiveness to long-term collaborative relationships with their suppliers and customers (Sheu, Yen, & Chae, 2006; Liker & Choi, 2004).

Despite this craze, collaboration remains a polysomic and elusive concept. This greatly limits the logistics managers’ ability to engage in collaborative operations (Saeed, Malhotra & Grover, 2005). In the same context, the determinants of collaboration have been the subject of many conceptual and empirical developments without a consensus emerging from this research. The literature identifies four main determinants: satisfaction, inter-organizational trust, partner’s engagement, and information sharing.

The following article first proposes, in the literature review, a conceptual distinction between the mechanisms that lead companies to collaborate. This leads to proposing a conceptual model and formulating the subsequent hypotheses. Then, the methodological framework of access to the real and the main results are presented. This article concludes with a number of avenues for nourishing research dynamics on the subject.

Literature Review and Theoretical Framework

The mobilized literature review highlights four collaboration determinants: companies economic and social satisfaction, inter-organizational trust partners commitment and information sharing.

Economic and social satisfaction

Satisfaction in Business to Business is today the subject of a rich mix of theoretical and conceptual discussions. Empirical investigations on its antecedents and consequences (Llosa, 1996) has been undertaken in this context. The first marketing satisfaction surveys date back to the seventies and were conducted in response to the resurgence of the consumerist movement of the sixties in the United States. A first trend was indeed founded and was interested in the dissatisfaction of consumers, using mainly descriptive methods. Satisfaction was then the subject of correlational approaches, using multi-attribute models. All of this pre-scientific research gradually gave way to the model of the reversal of expectations. This model proposes a cognitive conceptualization of satisfaction and states that it results from a comparison between pre-established standards and the perceived performance of the service or product consumed or used. When the perceived performance is higher than the expectations, satisfaction is followed, in the opposite case, there is dissatisfaction. There is indifference when perceived performance equals expectations. Gradually, the generalized model of denial integrates affects and emotions into the definition of satisfaction. Thus, the latter is defined as an emotion or the evaluation of an emotion and not only as cognition (Sirieix & Dubois, 1999). Let’s remember that satisfaction is the keystone of all the definitions given to the marketing concept.

In the supply chain, Brown Lusch, Robert and Darrel (1991) define satisfaction as a positive and emotional response to the economic benefits (commercial and financial reductions, payment delay, delivery delay, etc.) arising from the relationship with a partner. In other words, satisfaction is a company's judgment on a reward in relation to all the sacrifices made for the possession of a product / service. Satisfaction is indeed a kind of a buyer's cognitive state who feels sufficiently (or insufficiently) rewarded by his act of purchase.

Jap and Sanesan (2000) note that the turnover achieved through the sale of the partner's products and the financial results are the main drivers of economic satisfaction. These elements result from an economic behavior of the partner (Ho, Lim, & Camerer, 2006). In the same context, Geyskens and Steenkamp (2000) define economic satisfaction as an evaluation of the economic results resulting from an exchange relationship with a partner such as the volume of sales achieved thanks to a good quality of the purchased products, commercial reductions. (rebates and discounts granted by a supplier to his client as a recognition of the importance of the relationship, quality of the delivered products, adequate delivery and replenishment times, short payment terms). In this research, this definition has been retained. It fits perfectly with the classic objectives of logistics known as the 5 G's: Good product, good price (cost), good time, good place and good quantity.

In addition to the economic dimension, a second dimension, namely social or non-economic satisfaction, is underlined (Geyskens & Steenkamp, 2000). It is defined as a positive affective response resulting from the evaluation of the psychosociological aspects of the relationship, meaning if the interactions with the partner are fulfilled and satisfying. These dimensions are intrinsic in subjective aspects such as social contact, communication, shared values, trust, engagement partner, exchange…etc. Thus, non-economic satisfaction is the evaluation of interactive experiences with a partner. (Scheer & Stern, 1992). Note that the non-economic or social dimension corresponds to the affective or emotional dimension of any relationship. It refers to the feelings that exchange partners develop for each other and their emotional engagement in the relationship.

Trust

Historically, trust emerged in the field of psychology with the publication of a founding article "trust and suspicion" by the psychologist Deutsh (1958), and it quickly spread afterwards and was used in other fields. Then, a variety of scientific disciplines tackled this concept: psychology (Deutsh, 1958), sociology (Fukuyama, 1995), marketing (Morgan & Hunt, 1994), and not to forget strategic management and organizational behavior. It is considered as a central element in market transactions and relations between economic partners (Brülhart, Barrios, Elliott, & Sensier, 2003) and has become an unavoidable dimension in inter-organizational issues (Bidault & Jarillo, 1997).

Rizopoulos and Borzeda (2001) emphasize that it is difficult to apprehend long-term relationships formation without resorting to the notion of trust. Moreover, Spekman Kamauff, & Myhr, (1998). considers that collaborative behavior requires high levels of trust, commitment and information sharing among partners.

In the supply chain, the authors (Morgan & Hunt, 1994; Doney & Cannon, 1997; Nicholson, Compeau, & Sethi, 2001) concur in confirming two dimensions of trust.

Partners’ honesty

Several terms to describe this dimension exist, for example credibility, sincerity, reliability, loyalty, integrity. Honesty refers to the belief that the exchange partner will respect the ethical standards, in his ability to perform his job effectively, quickly and in keeping his word and being sincere.

Partners’ Benevolence

Benevolence refers to the belief in the business partner’s willingness to be concerned about his or her interests and those of his or her partner, to have beneficial actions in case of any emerging problematic situations or unforeseen circumstances that could harm the relationship (Ganesan, 2000) and will not engage in opportunistic and dishonest behavior. Thus, he or she must be motivated by looking for mutual gains achievement.

The commitment

Engagement is seen as the ultimate stage of business-to-business relationships (Dwyer, Schurr, & Oh, 1987). It is an important variable for the efficiency and effectiveness of relationships between members of the supply chain. This concept is often associated with trust: the level of trust depends on the level of inter-firm engagement (Morgan & Hunt, 1994; Kwon & Suh, 2004; Kwon & Suh, 2005).

The structural factors leading to the engagement of supply chain members are satisfaction, trust, non-recoverable or specific investments, technology and information sharing, adaptive capacity and flexibility (Wilson, 1995). The main research focused on trust or commitment in the consumer / brand relationship and a finding of deficiency is noted regarding the research in Suply Chain Management. Similarly, Supply Chain researchers have drawn inspiration from the work done in B to B marketing, namely distribution marketing and industrial marketing.

Information sharing

The concept of information has attracted a considerable attention from researchers in different disciplines of management science. Since nineteenth-century economic theories and particularly the paradigm of intelligence - modeling - choice, information is directly related to decision-making. In other words, the quality of information depends on the quality of the decisions made by the leaders and ultimately on the organizational performance. In this context, this paradigm reinforces the Structures-Behavior-Performance industrial economy approach. The environment structures as an information pool determine the behaviors (decisions and choices) of the leaders that affect the organization’ performance.

With the advent of Information and Communication Technologies (ICT), infobesity or informational opulence has been identified: an overabundance of available information. Unfortunately, this information forms a very heterogeneous and disparate set. In Supply Chain Management, Tai (2011) distinguishes three types of information sharing effects: Effects on the performance of the supply chain, effects on the development of the members’ sustainable competitive advantage and effect on the company’s overall performance.

Researchers that analyze the first effect emphasize that information sharing is a fundamental element to improve coordination and collaboration between upstream and downstream members of the supply chain. In this context, Chan and Chan (2009) affirm that the sharing of information is fundamental to coordinate and boost the supply chain activities.

Authors discussing the second type of effects envision information sharing as the scope by which reliable and relevant information is communicated to supply chain partners. From this perspective, the exchange of information is seen as a mean to improve collaborative relationships (Fawcett, Osterhaus, Magnan, Brau, & McCarter, 2007).

For the third type of effects, information sharing is seen as a relationship governance mechanism to create a sustainable competitive advantage for supply chain companies (Tai, 2011).

These companies can be suppliers of raw materials, companies manufacturing components, intermediate products or finished products, logistics service providers, and even the end customer. Companies are increasingly dependent on upstream and downstream processes, and are increasing information exchange with their suppliers and customers. Information and communication technologies (internet, intranet, local area networks (LAN), metropolitan area networks (MAN), wide area networks (WAN), etc.) and electronic information interchange allow nowadays an information system to communicate with another information system, using minimal human intervention and cost.

Similarly, the sharing of information does not lead to the creation of a competitive advantage but rather the way in which this information is exploited. In this context, Schroeder and Flynn (2001) affirm that the use of information-sharing technologies is not sufficient to achieve superior performance, but rather the sharing of relevant, reliable and comprehensive information.

The information sharing can be done with suppliers, the customer, the distributor, the retailer. Several indicators are used to assess the quality of the exchanged information: precision, census and frequency (Neumann & Segev, 1979), decision-making reliability (McCormack, 1998) and completeness (Li & Lin, 2006).

From the foregoing, the conceptual model and subsequent research hypotheses can be formulated as follows:

Figure 1: Conceptual Model
Conceptual Model
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H1- The greater the economic satisfaction of the partners, the important the collaboration is.

H2- The more satisfactory the social satisfaction is, the important the collaboration is.

H 3- the more honest the partners are, the more important the collaboration is.

H4- The benevelonce are the partners, the greater the collaboration is.

H5- The calculated commitment of partners has an effect on the collaboration

H6- The emotional commitment of partners has an effect the on collaboration.

H7- The more partners share information, the more important the collaboration is.

Research Method

On an operational level, the theoretical framework outlined above justifies the use of a quantitative methodology. The latter leads initially to choose the mobilized variables’ scales of measurement, to make sure of their relevance by proceeding to the validation of their contents with the professionals, to pre-test the questionnaire with a test sample before administering it on a large scale. The collected data were purified using exploratory factor analyzes (2013).

Items and questionnaire design

Due to the wide range of measures developed for the same variable, several criteria governed the choice of items. The number of times the article is cited. For this purpose, Social Science Citation Index and Google Scholar were used, the recency of measures and their psychometric qualities (De Jong, Steenkamp & Veldkamp, 2009), the number of items must be reasonable to not burden the questionnaire and be reflective rather than formative. Finally, the items developed in the same field of study were favored.

It should be noted that the Anglo-Saxon measures, the translation procedure and the retro translation have been applied. It consists initially of translating the original scale from English to French. Then the generated items are translated in reverse. If this second translation allows to find the original scale, we keep the items if not we correct by proceeding to iterations.

The economic and social satisfaction of companies has been operationalized by the Geyskens and Steenkamp (2000) scale. This scale includes 4 items for each dimension. For the measure of confidence, the Doney and Canon scale (1997) was selected. It includes 4 items for honesty and 3 items for the benevolence of the partners. Emotional commitment and calculated engagement were measured by the Morgan and Hunt scale (1994). It includes respectively 3 and 4 items. To operationalize the information sharing variable, the items developed by Li and Lin (2006) and Klein and Rai (2009) were used. The latter includes 5 items. Finally, the collaboration is measured by the scale of 5 items. Response scales are five-point Likert type (from 1 - strongly disagree - to 5 - strongly agree). In total, our questionnaire includes 32 items.

To ensure the validity of content, the list of items was submitted to two logistic managers. Following the recommendations of Jolibert and Jourdan (2006), they had to appreciate each item as "very", "somewhat" or "little" representative of the dimensions to which they were attached. Similarly, officials were asked to comment on the clarity of the proposals. The objective assigned to this step is to verify the relevance of the selected measures. Following this step, the wording of certain items was reworded because they were considered ambiguous and equivocal. Also, it has been proposed to replace "your supplier" with "your main supplier".

After testing with 21 companies located in the free zone of Tangier, the final questionnaire was administered by mail and using google drive from a sample of 210 industrial companies. After reminders by mail and phone, the responses of 135 questionnaires were exploited.

Exploratory factor analysis

Purification is an indispensable prerequisite of the hypothesis test. It is generally done by the exploratory factor analysis techniques, the most used of which is the principal component analysis (Hair et al, 2013).

In fact, it consists in studying the items’ importance in the formation and explanation of the variables to which they are attached. Three elements are examined: the commonalities or loading, the explained variance of the factors and the internal coherence of the scale measured by Cronbach's alpha. The results of the purification are given in the following table.

Table 1 -
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Table 2 -
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Findings

To test the research hypotheses, the multiple linear regression method has been applied. The results are shown in the table 2 .

When reading the results in the table above, several remarks can be made. The explanatory variables contribute in explaining 52% of the total variance of the supplier's collaboration (adjusted R² = 0.517). Honesty (Beta = 0.444, t = 10.869, p = 0.000), affective commitment (Beta = 0.274, t = 7.028, p = 0.000) and social satisfaction (Beta = 0.152, t = 3.906, p = 0.000 ) and economic satisfaction (Beta = 0.337, t = 2.963, p = 0.000), information sharing (Beta = 0.359, t = 2.452, p = 0.000) positively influence the suppliers-clients collaboration. The more honest they are, the more information they exchange, emotionally engaged and economically and socially satisfied, the more important their level of collaboration is. These results lead then to validate the hypotheses H1, H2, H6, H3 and H7. Similarly, honesty and economic satisfaction are the two elements that influence collaboration the most, the Beta coefficient is 0.444 and 0.337 respectively. This result corroborates the work already done in other countries (Ghosh & Fedorowicz, 2008), which emphasize that honesty is an essential ingredient for establishing collaborative relationships. Similarly, several authors (Goffnett et al., 2012) have confirmed the results of supply chain satisfaction’s work, particularly economic satisfaction.

Also, the information sharing, in view of the presented results, plays an essential role in the explanation of the supplier-client collaboration. This result corresponds to our anticipation and is already proven by previous research. "Without information sharing, collaboration can’t emerge," say Li and Lin (2006).

These results seem obvious. In the development stages regarding the relationship with the client, the authors (Dwyer et al, 1987) emphasize these elements in the first stage and as a prerequisite for succeeding the next steps for further collaboration and partnership.

Emotional commitment and social satisfaction are also present to explain the supplier-client collaboration. In fact, these two variables go hand in hand to explain collaboration. They reflect the subjective aspect that comes naturally after the objective aspect of the relationship.

However, the results of the collaboration’s regression on the calculated commitment (Beta = 0.008, t = 0.259, p = 0.96) and calculated benevolence (Beta = 0.009, t = 0.281, p = 0.778) demonstrate a very weak relationship between these variables and Student's "t" is well below the recommended threshold (1.96). In other words, calculated commitment and benevolence do not have a conclusive effect on collaboration. This leads to rejecting the underlying assumptions namely H4 and H5.

Conclusion and Discussions

To analyze the phenomenon of collaboration in the context of the supply chain, research in management sciences is largely based on a hypothetical-deductive approach. The mixed results of this work constituted a significant theoretical basis in our research.

The results of our work helped establish a hierarchy of the collaboration determinants in order to establish relational strategies that underlie the success of this phenomenon. Thus, the honesty, the seriousness and the credibility of the companies turn out to be the major determinant of the collaboration. The ability of managers to demonstrate these characteristics is in place to establish collaborative relationships that can build a good logistic performance of both the company and the logistics chain, and consequently the organizational performance.

Secondly, the economic nature of relationships also plays an important role in establishing collaboration. As such, highly competitive prices, the time of payment, delivery, mode and means of payment ... are all elements for long-term relationships’ success between companies

The emotional and affective aspect is present in any human relation but comes in third position. This explains why logistic managers are more concerned with the hard aspect of the relationship and that if it is collaborative; it is because companies are able to generate very significant economic benefits. Some authors (Shew, 2010; Fugate, 2010) refer to this relationship as pseudo-collaboration. These authors assert that in collaboration, the emotional aspect must be strongly present.

To conclude, the prioritization of the collaboration’s determinants helps identify the priorities for a relational strategy implementation to achieve a higher level of logistical and organizational performance. It is the responsibility of the buying and selling business to train logistics managers to be honest and available, and to get companies to base their competitive advantages on costs so that they can compete at competitive prices.

Our research shows a number of limitations that constitute avenues of research. The first limitation concerns the collaboration’s determinants. It would be wise to consider future research on other collaboration’s determinants than those identified in this paper, namely opportunistic corporate behavior and asymmetric information.

The choice of the sample could be a source of bias. Our choice has been made according to the empirical method in a reasoned way, but several authors advocate the stratified random method.

A final limitation is the analysis techniques and the hypotheses validation. Recall that multiple linear regression techniques were used. However, in models, it is common to validate the model as a whole. To do this, it is recommended to use structural equation techniques with latent variables and measurement errors. These techniques are also referred to as second- and third-generation statistical techniques that are used to turn the model through the use of incremental, absolute, and sparse adjustment indices. These indices are calculated using softwares such as Analysis of Moment Structures (AMOS) , Linear Structural Relations (LISREL) or Statistical Analysis System (SAS).

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Publisher

Future Academy

First Online

18.12.2019

Doi

10.15405/epsbs.2019.01.02.66

Online ISSN

2357-1330