.IJSBA.2015.06930_984149407064.pdf

Int. J. Strategic Business Alliances, Vol. 4, No. 1, 2015 1

Copyright © 2015 Inderscience Enterprises Ltd.

Why do both marriages and strategic alliances have over 50% failure rate? A study of relationship quality of strategic alliances in China, Japan and Mauritius

Mosad Zineldin* Strategic Relationship Management, Linnaeus University, SE-35195 Växjö, Sweden Email: [email protected] *Corresponding author

Hisao Fujimoto Faculty of Information Technology and Social Sciences, Osaka University of Economics, 2-2-8, Osumi, Higashiyodogawa-ku, Osaka, Japan Email: [email protected]

Yu Li School of Economics and Business Administration, Beijing Normal University, Outer St. 19, Xin Jiekou, Beijing, China Email: [email protected]

Hemant Kassean Faculty of Law and Management, University of Mauritius, Reduit, Mauritius Email: [email protected]

Valentina Vasicheva School of Business and Economics, Linnaeus University, SE-35195 Växjö, Sweden Email: [email protected]

We Feng Yu University of Shanghai for Science and Technology, 516 Jungong Rd, Yangpu, Shanghai, China Email: [email protected]

2 M. Zineldin et al.

Abstract: This research explores the importance of quality variables for achieving high quality in strategic alliance relationship, reasons for strategic alliance failures and provides insights into their underlying causes. Data for analysis is generated from 112 managers from different industries in three countries. Frequency, factor, and regression analysis, reliability tests are used for data analysis. Multiple item scales based on five qualities model (5Qs) were developed and adapted. The results suggest that there is an important interaction between most independent variables and alliance motivations, length and type of alliance. Quality of atmosphere followed by quality of interaction was identified as the most important variables to achieve high total quality of strategic alliance relationship (TQSAR). The proposed 5Qs model consists of some generic and integrated dimensions. Each quality dimension is represented by a number of statements/items, intended to represent a specific quality factor as thoroughly and reliably as possible.

Keywords: strategic alliances; total relationship management; TRM; 5Qs; marriage; failure; psychology; quality; strategic business alliances.

Reference to this paper should be made as follows: Zineldin, M., Fujimoto, H., Li, Y., Kassean, H., Vasicheva, V. and Yu, W.F. (2015) ‘Why do both marriages and strategic alliances have over 50% failure rate? A study of relationship quality of strategic alliances in China, Japan and Mauritius’, Int. J. Strategic Business Alliances, Vol. 4, No. 1, pp.1–23.

Biographical notes: Mosad Zineldin is a Professor of Strategic Relationship Management at the Linnaeus University, Sweden.

Hisao Fujimoto is a Professor of the Faculty of Information Technology and Social Sciences at the Osaka University of Economics, Japan.

Yu Li is a PhD candidate of the School of Economics and Business Administration at the Beijing Normal University, China.

Hemant Kassean is a Senior Lecturer of the Faculty of Law and Management at the University of Mauritius.

Valentina Vasicheva is a Lecturer of the School of Business and Economics at the Linnaeus University, Sweden.

We Feng Yu is a Professor at the University of Shanghai for Science and Technology, China.

1 Introduction

The problem of achieving cooperation among human beings is hardly new. Plato and Caesar are perhaps as good analysts of cooperation as today’s management scholars. Inter-organisational cooperation and strategic alliance are hardly new either. So, why today’s recovery is of interest?

Few, if any, phenomena in public or private management and organisation have raised so much scholarly attention in such a short period of time as strategic alliance relationships. Many studies and researches indicate that between 50% to 77% of mergers and strategic alliances (SA) fail (Porter, 1987; Cartwright and Cooper, 1995; Park and

Why do both marriages and strategic alliances have over 50% failure rate? 3

Ungson, 2001; Valant, 2008). Strategic alliance failure (SAF) often causes serious damages and several adverse effects to the partners such as disagreements, operational difficulties and problems, transaction costs to find new partners, anxieties over the loss of proprietary information and also intangible adverse outcomes such as the loss of reputation (Park and Ungson, 2001; Hamel, 1991; Zineldin and Dodourova, 2005). Relationship between people has many common factors with relationship between organisations (Sambasivan et al., 2012). Zafirovski (2005) states that a relationship between organisations contains not only utilitarian economic factors but also psychological behavioural factors (Cartwright and Cooper, 1993, 1995). Social exchange theory (SET) is based on economical and psychological behaviourism because the establishing, developing and sustaining human or inter organisational relationships goes beyond the utilitarian economics.

Inter-organisational cooperation can be examined from a wide range of theoretical starting points. They include strategic management, organisation theory, economic and industrial analysis, network theory, game theory, the sociology and psychology theories, to name only the most obvious. Models of bilateral (e.g., marriage) and multilateral (e.g., multi-state coalitions) relationships can also be applied to the study of inter-organisational collaboration. May and Tate (2011) found evidences that cooperative alliances are determined by economic and social-psychological variables. More interestingly, the collaboration phenomenon challenges researchers to extend these theories by highlighting the complexity of the inter-organisational relationships. This makes strategic alliance research intellectually challenging. This new situation was brought about by the radical changes in the global economy (Zineldin, 1998; Zineldin and Bredenlöw, 2003; Paavo and Hallikas, 2011).

Cartwright and Cooper (1993, 1995) stated that although there is a well-recognised and powerful strategic argument for different partnering types such as merger and joint ventures for competitiveness, the conventional strategic wisdom alone is an insufficient catalyst for releasing or achieving the synergistic potential of many promising organisational marriage.

Considering the constant growth of the number of SA in the world and despite high percentage of failures, it seems that the reasons, which can cause a failure of a strategic alliance, have to become a focus of special attention. Although the increased interests of managing SA, the field still theoretically and empirically lacks a framework to describe the conditions and dynamics leading to the failure of SA (Park and Ungson, 2001; Zineldin and Dodourova, 2005; Valant, 2008).

Trust and cooperation are critical factors that affect level of the success or failure of SA (Mellat-Parast and Digman, 2008). Prajogo et al. (2012) found that there is a positive correlation between the strategic long-term relationship between partners on firm’s operational performance which impacts on its delivery, flexibility and costs performance.

While previous research on quality and quality management has focused on the implementation of quality management within a firm, by extending the concept of quality management to SA, this paper takes a new approach toward total relationship management (TRM) implementation outside the traditional view towards quality. According to our knowledge, there is no research of how to measure strategic alliance relationship quality (SARQ), determinants, and its consequences based on the comprehensive 5Q dimensions. Thus, the main task of this research is to measure the quality of the strategic alliance relationship (QSAR) and identify the key factors that


influence strategic alliance outcomes. The aim is to avoid the reasons for failures of SA. The correlation between the nationality (culture), the size of the organisation, the alliance motivations and the quality of the strategic alliance relationships (QSAR) are analysed. The 5 Qualities (5Qs) model and approach are utilised to measure, identify and categorise the QSAR. Through the study of the quality of the existing alliance relationship one can draw some conclusions about the possible reasons of failures and the conditions under which strategic alliance became a competitive weapon.

It is a cross cultural research which considers different industry sectors located in different countries – China, Japan and Mauritius. The choice of the countries is a result of our networks with different researchers in the above mentioned countries and the availability and access to the needed data. As part of the study, CEOs from Mauritian industries also participated in the survey. Although a small country in size, Mauritius is classified as a middle income country with an emergent consumer market and ranks first in Africa for global competitiveness (World Economic Forum, 2013). It is often cited as an example for the African continent. The geographical spreading and cultural differences provide a good base for the generalisation of the study results and outcomes. The results will let the partners know whether their relationship has the strength to withstand the ultimate tests of time and stress.

2 Romance and business

None of us, nor any company, exists in isolation. A relationship between people often goes through different stages (e.g., growth, maturity) in its life cycle. Relationships between companies too, are assumed to go through various phases. Many of the choices we make and reactions we have are in response to the actions of the other people. In business markets companies are also often dependent for their development and success on their relationships with others (Zineldin, 2002).

In many ways, a partnership business relationship is similar to a romantic and marriage relationship. Corporate entities are much like two people who engage with each other in what they hope to be a long-lasting and mutually satisfying endeavour. Like a romantic relationship, a strategic alliance relationship (SAR) progresses through a natural evolution pattern or relationship life cycle that requires awareness, understanding, flexibility and agreement from both parties in order to enjoy prosperity (Zineldin, 2002).

Haubrich (1989) describes enduring relationships between banks and borrowers as a long-term marriage relationship. Zineldin (2000) contributes to the research area by showing that building and enhancing a relationship is similar to that of a romantic and marriage relationship. This relationship is a dynamic process which demands actions, interactions, trust, cooperation, adaptations and commitment. Narasimhan and Nair (2005) argue that trust, information sharing as well as quality expectation between partners positively impacting strategic alliance performance.

An example of corporate love affairs is McDonald’s relationships with Coca-Cola. When McDonalds CEO Mike Quinlan talks about this alliance his eyes light up. He gushes, using a tone that says it all: “They are our partner. It’s an enormously important strategic alliance…” Like any affair of the heart, the two companies loved getting away together for a special weekend every now and then (Fortune, 1994).

Song and Liu (2012) underline the importance of understanding the nature of relationship value and to model and measure the value of business relationships. There


are two basic issues about relationship value: what makes business relationships valuable and how the value of business relationship can be assessed (Corsaro and Snehota, 2010). You’ve probably heard this in the workplace or in a marriage: “I don’t know what I want, but I’ll know it when I see it”. That may work when buying art, but it is a recipe for failure in achieving positive results in a business or marriage (Valant, 2008). Harmony between the couple in marriage as well as between business partners with different cultures and attitudes have direct impact of the quality of a such relationship. Inter-organisational harmony has direct and indirect impact on the cooperation atmosphere and the performance of the partners (Chow and Yau, 2010).

The relationship of the partners, as in a marriage, is a key to the success of the arrangement. It may not be a sufficient factor itself, since the successful alliance needs positive quantifiable results, but it is certainly a necessary condition. This romantic business philosophy assumes that, love affairs or marriage relationships as well as long-term business relationships are as ideally based on shared interest, mutual trustworthiness, ethics, cooperation, and commitment to continue the relationship and to keep the relationship arrangement productive, mutually beneficial and rewarding for all parties.

Finally, Valant (2008) states that marriages, SA and mergers end up on the rocks 50% of the time. Many management relationships, like husband and wife pairs, end up in such irreversible trouble that one person simply has to go – or let go – often without a severance package. One example of uncomfortable business marriage was the case of Ford and Volkswagen alliance in the 1980s. Although there was a common goal to expand their market into emerging Latin America’s. The alliance was a non-romantic and uncomfortable marriage from the beginning because the partners were direct competitors in most other markets and they were not willing to share their own design skills and marketing strategies with each other. Although both were from advanced countries, differences in cultural values and organisational practices were barriers against developing a coherent strategy to challenge GM, who was a major competitor in the market (Park and Ungson, 2001). Volvo and Renault in the 1980s and Volvo - Ford in the 1990s alliances were similar to the case of Ford – Volkswagen which has ended with a divorce or alliance collapse. One common factor was that there was a good motive, but the outcomes were negative.

3 Strategic alliance and TRM

It is apparent from the literature review that despite the increasing importance of international relations and business, insufficient attention is being paid to exploring and theorising relationship management (RM) application on the SA in international contexts. The application and use of RM and SA is of considerable interest to both industry practitioners and academics. However, recent research has shown that the balance between theoretical and practical knowledge concerning RM and SA is far from equivalent. Total RM suggests new way of understanding the different international business environments and, as a result, diverse ways of interacting with them. Both the academic as well as the managerial world have much to gain by studying and understanding these types of exchanges.


According to Chandler’s (1982) definition, strategy is “the determination of the basic long-term goals and objectives of an enterprise and the adoption of courses of action and the allocation of resources necessary for carrying out those goals”. So, strategic alliances are entered into by two or more partners to pursue long-term goals beneficial for all the partners, and this characteristic differentiates SA from other forms of partnerships.

Although the prior strategic alliance studies have added to our knowledge of why SA forms the enablers for initiation success and the achieved benefits (e.g., Zineldin, 2002; Zineldin and Jonsson, 2000; Wheelen and Hungar, 2000; Lemoine and Dagnæs, 2003; Ghoshal, 1987; Dyer and Ouchi, 1993; Geringer and Louis, 1991; Brucellaria, 1997), most of these studies suffer from some weaknesses. Some have failed to use formative indicators to differentiate between failed and successful alliances, instead opting for either a descriptive case approach or respondent based reports of alliance existence. Most studies tend to focus more on the determinants of their success rather than on the reasons they fail. The main result of previous studies on SA and RM showed that there are noticeable differences in the motives for entering into an alliance (Zineldin, 2005). The studies also indicated that there is little support for the hypotheses that culture differences act as a hindrance or reason for failure of SA or business relationships and point out to the continued need for a holistic view of identifying formative indicators and examining risks and problems associated with entering and maintaining successful strategic alliance. TRM is a philosophy developed by Zineldin (1999) which emphasises the holistic view which focuses on the internal and external factors impacting a relationship or a strategic alliance (Arslan, 2008). A TRM is viewed as a strategy and a philosophy. It is ‘total’ because it considers and coordinates ‘all’ today’s and future internal and external activities and resources involved in getting, keeping, enhancing and satisfying customers and maintaining quality. It is a strategy because it emphasises maintaining high quality products/services, internal and external relationships and trying to keep customers on a long-term basis. It is a philosophy because it should be used to communicate the idea that a major goal of management is to continuously improve the total quality and to plan and build appropriate close and flexible long-term relationships with the parties who contribute to the organisation’s success and long-term sustainable growth. It should also guide the overall thinking of the organisation, its decision making and the execution of predetermined plans. That is why Zineldin et al. (2012) also called this approach a total strategic relationship management and philosophy. Arslan (2008) argues that the idea of ‘total’ in literature was first introduced by Zineldin (1999) because it considers and coordinates ‘all’ activities-including internal and external relationships, networks, interactions and collaborations as well as all activities involved in getting, keeping, enhancing and satisfying customers throughout quality.

Strategic alliance requires a holistic view and TRM approach to be able to cooperate and coordinate different resources, activities and strategies (Zineldin, 2000). TRM according to Solomon (2005) is an all-inclusive approach which is useful for developing and promoting an effective philosophy of coordination of internal and external auditing systems which needs to have a vision of what it wants to achieve through coordination and may even consider its incorporation in the core goals or objectives of the organisation. Under the paradigm of TRM, the firm focuses on all integrated activities within the organisation, including internal and external relationships (Gupta et al., 2005). The TRM raises several important issues regarding the various motives for establishing a long term relationship or forming alliances with respect to competitive advantage and the


likelihood of a manufacturer entering into alliances with different partners. Alliance motivation has an important role in alliance performance and outcomes.

Nationality of the partners influences the beliefs about and behaviours of the alliance partners. However, the culture is also influenced by the complex inter-relationships between relational constructs such as trust, commitment, cooperation, dependence, communication, adaptations, financial and social exchanges (Bhaskaran and Gligorovska, 2009; Zineldin and Dodourova, 2005). According to Tayeb (1994), 70% of organisational behaviour and human resource management literature make references to culture and nearly 94 % of these studies conclude that culture influences organisational behaviour including strategic alliance formation, acquisitions and mergers.

Zineldin and Dodourova (2005) and Hongbin (2012) have concluded that the cultural difference has no significant impact on alliance performance. Das and Kumar (2010) argue also that cultures of the partner firms, the context of cooperation, and the prior experience of firms in managing alliances, may also play a role. They stated “Managers socialized in these cultures will be more tolerant of disruptions and the instinctive reaction will not be to try to control the disruption. They will go with the flow, seeking to adapt to the ongoing environment”.

The quality of the alliance relationship is not only influenced by nationalities and cultures but also by the experience, previous termination, alliance type, organisation size and age. Size of the organisation influences the strength of the alliance relationship. Larger companies tend to gain greater benefits from the relationship than smaller firms (Terziovski and Samson, 2000). Based on organisational learning theory, length of alliance, experience of having alliance with different partners type of alliance form affect the success rates of SA (Anand and Khanna, 2000; Heimeriks and Duysters, 2007). Rothaermel and Deeds (2006) found that alliance type and alliance experience moderate the alliance relationships and product development. Even, the termination of the previous alliance relationships refers to the capability and unique knowledge that firms deploy for the formation, management, and termination of alliances (Lambe et al., 2002; Ziggers and Tjemkes, 2010).

4 Relationship quality

Studies in marriage and love relationship show that there are four dimensions of relationship quality: intimacy, agreement, independence, and sexuality. Many of these studies concluded that relationship satisfaction was well predicted by these four scales, with intimacy contributing most, and sexuality least, to overall relationship satisfaction (Hassebrauck and Feh, 2002; Myers and Diener, 1995). The four scales correlated as predicted with other constructs relevant to close relationships, such as commitment, trust and other such soft behavioural and psychological variables (Hassebrauck and Feh, 2002). We assume that the intimacy, agreement and independence dimensions are relevant for the SARs. This is an important undertaking given that the quality of a marriage as well as of a strategic alliance intimate or long term relationship has manifold consequences for not only institutional finance and economic aspects but also psychological well-being of an individual.

Relationship quality has been suggested as a result of measuring the positive relationship (Crosby et al., 1990; Fynes et al., 2005). Understanding the perceived


relationship quality is critical to predict the firm’s future interactions with its partner as well as the healthiness of the existing relationships (Choo et al., 2009). Based on TRM approach, Zineldin (2000, 2006) developed a new measurement model which includes five generic quality dimensions (5Qs) framework to measure the quality of both marriage/romance or SAR. The 5Qs model is a comprehensive instrument that assures reasonable relevance, validity and reliability, while being explicitly change oriented. The interaction process between relationship partners is influenced by specific environmental atmospheres where both operate (Ford et al., 1998; Zineldin, 2004; Robicheaux and El-Ansary, 1975). The atmosphere can affect perceived relationship quality by improving or by making it worse, which affects the overall negative or positive outcomes of the strategic alliance.

Some key episodes or variables of the structure of relationship quality are adaptation, communication, commitment, conflict, cooperation, expectation of continuity, interdependence, bonds, opportunism, relationship stability, satisfaction, trust, and willingness to invest in the relationship (Huntley, 2006; Moon, 2007; Zineldin, 2000). The age, culture, motive and experiences of the partners influence the expecting outcome of the relationship performance and total quality of strategic alliance relationship (TQSAR). The same should take place in the business world according to Zineldin et al. (2012).

Figure 1 illustrates the z5Qs model and its constructs where the TQSAR of the partners overall satisfaction is a function of Q1–Q5. The model is based on the total relationship approach (TRM). The TQSAR = fn(Q1+ Q2 + Q3 + Q4 + Q5). Moreover, there is a sequential relationship between the 5Qs, as shown in the following figure.

Figure 1 Zineldin’s 5Q constructs model (see online version for colours)


4.1 Relations, correlations and significance between factors impacting the TQSAR

Q1 Object – technical quality (which measures the justification and main motivations of entering into a marriage or SAR. The motivations can be one or all of the following financial, technological, managerial and strategic. The positive aspects and outcomes of construct of relationship factors should significantly outweigh the negative ones.

Q2 Processes – functional quality (how the partners established and enhanced the relationship). It measures how well relationship activities are implemented. Adaptation is important Q2 factor. Partner A could change its own product design to cope with a production difficulty at its partner B (e.g., a supplier). Adaptation could also include investment of tangible and intangible resources by both parties. This investment ranges from the use of human resources to develop contacts with the counterpart.

Q3 Infrastructure – basic resources needed to perform the core activities of the relationship. Commitment, keeping promises, integrity are some key Q3 variables. Core competences, skills and knowledge are also critical factors.

Q4 Interaction – communication and information exchange, financial and social exchanges between the partners are critical factors. Bonds also arise between any two interacting parties as they learn to deal with each other. The interaction process that characterises relationships can be said to be productive for the parties involved in the sense that they correct and develop their knowledge of the counterpart and learn to exploit each other and the relationship better. Different bonds could be classified as social, technical, timing, knowledge, planning, and legal/economic bonds (Zineldin, 2000). Termination costs can also be a bond.

Q5 Atmosphere – relationship and interaction process between parties are influenced by specific environments where they operate. Frank, cooperative or unfriendly atmosphere explains good or poor care. Consequently, atmosphere indicators should be considered critically. Shared values and visions are positive atmosphere factors. Opportunism is a negative variable. It can be defined as “self-interest seeking with guile” (Williamson, 1985). Examples of opportunistic behaviour are such acts as withholding or distorting information and shirking or failing to fulfil promises or obligations (Zineldin, 2000). Satisfactory atmosphere can lead to that one partner can make e to save the relationship from being ruined (divorce).

5 Methodology

5.1 Research design

Data was collected through a mail survey administered to senior executives of different size manufacturers and service providers in China, Japan and Mauritius. The diversity of countries, industries, sizes and ages of the organisation was designed to assure the possibility of generalisation of the research results and outcomes.


Following the literature review and questionnaire design, a pilot study was carried out in companies such as Volvo and Scania in Russia, DHL, JCI Suita and Chamber of commerce in Japan, White Sand Tours, Mauritius Telecoms, ICT companies in Mauritius and Sika from China. Respondents were encouraged to identify unclear items, comment on the importance of the research issues, if the respondents could/would complete the questionnaire in the absence of a researcher, and suggest changes. No major problems were presented, and after making the required modifications, the final draft of the questionnaire was developed.

5.1.1 The sample

The snowball sampling approach has successfully been used to gain respondents. According to snowball sampling, respondents are chosen from the professional and friendship networks of existing members of the sample (Thompson and Collin, 2002). The period of snowballing was four months (June–September 2012). The questionnaire was designed as web-survey with a link to the survey platform or portal on line and as an e-mail survey. The respondents were encouraged to login with the specific password to conduct online reply or to return the answered survey to the researchers e-mail. By beginning of September 2012 a total of 112 (N 112) full completed questionnaires were received from respondents had SA with different suppliers, distributors and other supply chain actors. The sample profile is presented in Table 1. Most of the respondents were primarily male (61.6%). Almost 44% had previous failure or experience of strategic alliance termination for different reasons. Table 1 Sample profile

N 112 Frequency Percent (%) Mean Std dev

Gender of the senior executive 1.38 .489 Male 69 61.6 Female 43 38.4

Previous SA termination (divorce) 1.56 .498 Yes 49 43.8 No 63 56.2

Length of the alliance, SA (marriage) 1.66 .823 Long (over 15 years) 63 56.3 Medium (over 5 to 14) 24 21.4 Short (less than 5) 25 22.3

Size of the organisation 1.83 .899 Large 55 49.1 Medium 21 18.8 Small 36 32.1 Age of the organisation 1.29 .610 Old (over 20 years) 88 78.6 Middle age (between 5–19) 15 13.5


Table 1 Sample profile (continued)

N 112 Frequency Percent (%) Mean Std dev

Partner’s nationality (culture) 1.74 1.020 Native 64 57.2 European 25 22.5 USA 11 9.6 Others 12 10.7

The majority of the existing SA (56.3%) were very stable with long term partnership over 15 years. 78.6% of the organisations were mature enough (over 20 years old) and 8% are younger than five years old. 49% were large companies with over 500 employees and 32% are small with one to ten employees.

5.1.2 Scales

Scales consisting of multiple items were developed to measure each of the 5Qs construct. Given our conceptualisation of SAR major economic factors such as cost, profits, investment, market share and behavioural factors trust, commitment, flexibility, satisfaction, ethical and unethical behaviours, power and dependency it was essential that the quality measures of the strategic alliance relation (SAR) captured both the importance of the relationship to respondents and their beliefs about working to maintain the collaborative relationship and avoid or decrease the probabilities of the future failure. We draw upon scales which had been used in human relations such as in marriage as well as business relations marketing and management literature to further the process of validation for established scales. Listening to each other, openness, honesty, trust, and so on are scales for measuring the intimacy. They correspond to the intimacy dimension in Sternberg’s (1986) triangular theory of love. Features such as mutual goals, common activities, harmony, and security are some of the agreement which is similar to the dyadic consensus subscale from Spanier’s (1976) ‘Quality of Marriage’. Integrity, freedom and autonomy are some of the independence factors which are part of the relationship beliefs identified by Fletcher and Kininmonth (1992). Other scales were also based on the previous research such as perceived quality, business trust, commitment and satisfaction (Dwyer and Oh, 1987; Moorman et al., 1992; Zineldin and Jonsson, 2000; Zineldin, 2006; Skarmeas and Robson, 2008). The selection of these dimensions is also based on the suitability to the context of B2B markets. We have also developed some new, or adjusted, scales to perfectly suit the present study and are able to conduct high quality empirical research. All constructs were measured through multiple-item scales and a five-point Likert-type response format.

The independent variables of this study are the 5Qs (Q1–Q5) and the dependent variables are alliance motivation (A2), previous experience and termination (A1), culture and nationality (A5), alliance type, (A9), and alliance length (A10). The control variables are the age and size of the organisation. Most of the 45 items and scales in the 5Qs constructs were already statistically verified and tasted in different business relations in different areas such as wood industry supplier-dealer long term relationship, strategic alliance between Swedish and Russian automobile manufacturer. Some of these factors were also tested to measure satisfaction in healthcare and educational sittings. The result


of such surveys was already published in different journals. Scales were created to represent the various constructs of interest based on prior work in the area. Majority of the scales had been tested on previous occasions and had been proven to be reliable (Akdag and Zineldin, 2010; Byrd, 2009; Morgan and Hunt, 1994; Meyer and Allen, 1984; Zineldin, 2006; Zineldin and Vasicheva, 2011) with Cronbach alpha values generally in excess of 0.85 and apparent simple structure as indicated from confirmatory factor analysis. Some new items based on sociology and psychology studies on marriage and family relationships are added. Some measurable quality scales of the 5Qs model are:

1 we often feel very satisfied in the cooperation with the partner

2 to succeed in this relationship, it is often necessary to have common goals and policies.

3 our future profits are dependent on maintaining a good working relationship with this partner

4 the partner spends lots of time to get to know our personnel and employees

5 this partner spends enough energy in our relationship

6 there is no reason for us to be suspicious to this partner

7 despite the busy lives and schedules, we make time to spend ‘quality time’ together

8 this partner is willing to adjust its production process to us

9 the partner gives us opportunities to participate in goal setting for performance

10 the partner will support our activities

11 this relationship requires maximum effort and involvement

12 we are fully open and honest in the relationship with this partner.

Piskar and Faganel (2009) and Tu (2009) provided empirical evidences that the 5Qs model and its scales emphasise that quality are used as the key aspect to survive and gain a competitive advantage by establishing long-term relationships.

6 Reliability and validity

Validity and reliability tests were performed to ensure that the scales were valid and were measuring what they were supposed to. It was also necessary to test the degree of internal consistency, or degree of inter-correlation among several measures for the same construct.

Cronbach’s coefficient alpha was used to assess the degree of internal consistency of within a particular scale. From a psychometric point of view, Alpha values of the 5Qs subscales for trust, commitment, cooperation, shared values, etc., have been validated in numerous studies, as well as in several different cultures, e.g., USA, Sweden, Turkey, Egypt, Jordan and Kazakhstan. According to Churchill (1979) and Fornell and Larcker (1981), 0.70 or higher are considered to be acceptable, with 0.60 being acceptable for new scales. As shown in Table 2, all scales exceeded this threshold. Some descriptive statistics such as mean and SD are also shown in Table 2.


Table 2 Item statistics

N 112 Mean SD Cronbach’s alpha Q1 Object 32.75 2.62 .79 Q2 Process 31.48 3.64 .76 Q3 Infrastructure 29.14 2.79 .79 Q4 Interaction 32.13 3.72 .77 Q5 Atmosphere 33.52 4.80 .77 TQSAR 159.07 14.80 .88

Our 5Qs scales of the 45 sub-items had a good reliability score (Cronbach α = 0.77). Construct validity was tested through factor analysis by principal components for respective scale. Factor analysis reduced 45 variables associated with the 5Qs model as attributes to ten new, salient variables. The eigenvalues were all larger than one and the majority of individual item loadings exceeded 0.5, with many loading in the around 0.70. These ten components explain a total of 81.49% for the variance. The results indicate that most of the scales used in the analysis will have good construct validity. The five highest loading factors are presented in Table 3. Table 3 Factor analysis

Q. type Highest 5 Load Q type Lowest 5 Load. Q3:1 Trust of the partner .777 Q3:5 Time to know our personnel .311 Q2:5 Common performance

goal setting .773 Q2.1 Flexibility and willingness to

adapt .337

Q5:4 Frequently possibilities discuss new

.772 Q4:6 Coordination routines of administrative

.346

Q4:4 Open and honest behaviour

.763 Q4:3 In advance information sharing .348

Q5:1 Enough energy to sustain SA

.756 Q5:8 Regularly check each other future plans

.351

7 Analysis and results

The following control variables were used in the study: 5Qs independent variables of object, (Q1) process (Q2), infrastructure (Q3), interaction (Q4) atmosphere (Q5) and dependent variables: length of alliance (commitment level), nationality (culture) of the partner organisation (native, European, USA, others), alliance type (11 types: such as joint venture, join R&D, distribution, product development, full merge, etc.), alliance motivation (A2) and if the organisation had previous termination of strategic alliance (divorce), age of the organisation (A5: old, middle age or young), size of the organisation (A3: large, medium or small). Table 4 shows the correlations between each of the dependent and independent variables. Majority of the bivariate correlations are positive and several of them are statistically significant. In particular, the correlations between the independent variables are all positive.


Table 4 Descriptive statistics and Pearson correlations confidents

Q1

Q2

Q3

Q4

Q5

A2

A3

A5

A8

A9

A10

A1

Q1

Obj

ect

1

Q2

Proc

ess

.666

**

1

Q

3 In

frast

ruct

ure

.638

**

.438

**

1

Q4

Inte

ract

ion

.603

**

.615

**

.642

**

1

Q

5 A

tmos

pher

e .7

05**

.6

45**

.7

02**

.6

89**

1

A

2 A

llian

ce m

otiv

e .1

34

.004

.0

51

.192

* –.

032*

1

A3

Org

. siz

e .1

01

.143

.1

37

.325

**

.142

–.

038*

1

A

5 O

rg. a

ge

–.02

1 .0

76

.308

**

.244

**

.191

* –.

075

.342

**

1

A

8 P.

nat

iona

lity

.060

.0

89

.051

.0

21

.144

–.

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As can be seen, the control variable size (A3) of the organisation is positively related to only one independent variable which is Q4 (interaction). It also positively related to the age of the partner organisation but negatively related to the dependent variables the nationality of the partner organisation and its previous experience of breaking or termination relations. The other control variable, age of the organisation is positively related to the independent variables Q3 and Q4 (infrastructure and interaction). Mature company use to have good infrastructure and interaction strategies to assure and maintain good quality of the relationship. The age is also negatively related to the nationality and termination ability of the partner organisation. The motivation of strategic alliance (A2: MOT) is positively related to the interaction (Q4) of the relationship. The quality of object is positively related to both type and length of the alliance relationship. Q2 and Q4 are related to the length of the relationship. Q 3 and Q5 are related to the type of the alliance. Although the dependent variables nationality (culture) was related to the control variable age and size, it was not related to any of the independent variables. Previous termination (divorce) of strategic alliance was related to only Q4 (INTER). One separate regression was conducted for each of the other four dependent variables, Motivation (MOT), alliance length (ALLNTH) alliance type (ALLTYP) and previous termination (TERM).

Each regression model are discussed in the following sections. The collinearity between several of the independent variables, and the high bivariate correlations between the independent variables and some of the dependent variables, resulted in the fact that several strong regression models could be developed. The models presented here, only contain statistically significant variables, and explain high levels of variance in the dependent variable.

7.1 Regression with alliance motivation (MOT) as dependent variable

Table 5 shows a resulting regression model with MOT as the dependent variable, and the identified independent variables. The model only involves statistically significant variables. The model explains 13% of the variance in strategic alliance motivation (MOT). Beta coefficient shows that independent variable Q4 makes the strongest unique contribution followed by Q5 to explaining the dependent variable MOT when the variance explained by all other variables in the model is controlled for. Q1 was lower (.32), indicating that it made less of a contribution. All Q1, Q4 and Q5 made a unique and statistically significant contribution to the prediction of the strategic alliance motivation. Table 5 Regression model for MOT (A2)

Variables b P R R2 0.362a 0.131 Q4 INTER 0.42** .003 Q5 ATMOS –0.36** .024 Q1 OBJ 0.32** .031

Note: *p < 0.05; **p < 0.01.

Interaction (INTER) is the most important variable in the model. It is not very surprising that a quality of the relationship depends on the partners’ willingness and good intention to maintain and develop the relationship. Thus, efforts and involvement to visit


and to know each other better and deeper improve the quality of interaction. Social, economic and knowledge exchange are also important for the interactions between partners. We find it more interesting that atmosphere (ATMOS) which includes making quality time to spend and having fun together is as important for the organisation as in the marriage relationship. The quality of the OBJ (Q1) which is the main reason for the cooperation was not making strong contribution as the INTER (Q4) and ATMOS (Q5). These are significant variables in the model but seem to be a given fact which means that if you do not provide good object there would not be any relation at all. These findings verify previous research (Zineldin, 2006; Zineldin et al., 2012) and further emphases the importance of the three variables to achieve a high quality relationship.

7.2 Regression with ALLNTH (A10) as dependent variable

Table 6 shows the results of a regression with the length of the strategic alliance as dependent variable. Length of the relationship is an indication of the relationship stability, maturity and commitment. We used scale long term (over 15 years), medium (over 5–14 years) and short (less than 5 years). Table 6 shows that three independent variables Q5 (atmosphere), Q2 (Process) and again Q1 (Object) are strongly related to the length of the relationship. INTER is not statistically significant in the model with ALLNTH as dependent variable, but it is still positively correlated with ALNTH (see bivariate correlation in Table 4).

Table 6 Regression model for ALLENTH

Variables b P R R2

0.504a 0.219

Q5 ATMOS 0.45** .003

Q2 PROC –0.42** .001

Q1 OBJ 0.33** .031

Note: *p < 0.05; **p < 0.01.

Although the three identified variables make up a very strong model for ALLNTH, the other independent variables may also be important for high-trust relationships. These findings verify previous research (Akdag and Zineldin, 2010; Byrd, 2009) and further emphases the importance of the atmosphere and the process variables to achieve a high quality SAR.

7.3 Regression with ALLTYP (A9) as dependent variable

Table 7 uses the mean value of ALLTYP as dependent variable. Table 7 shows the results of a regression with the same independent variables as in table 5, but with ALLTYP as dependent variable. The three models (Tables 5, 6 and 7) contain OBJ as important common underlying variables. INTER (Q4) is not statistically significant in the model with ALLTYP as dependent variable.


Table 7 Regression model for ALLTYP

Variables b P R R2 0.448 0.163 Q3 INFRA 0.34** .013 Q1 OBJ 0.33** .021

Note: *p < 0.05; **p < 0.01.

It is very logical that when selecting a soul mate or partners for stable relationship, one is more interested in the infrastructure of the expecting partners which reflects the potential sustainability of win-win relationship. Human and capital resources, competences and knowledge, honest behaviour, integrity are some important factors related to the atmosphere. Other variables are also important and significant but not in during the phase of partner selection.

7.4 Regression with TERM as dependent variable

The last regression model (Table 8) uses the previous termination as an indication of the failure of the previous strategic alliance or divorce between the partners. It shows that the most significant factor for the divorce is the interaction (INTER). The significance is weak and the model explains only 7% of the variance in TERM. Table 8 Regression model for TERM

Variables b P R R2

0.264 0.070 Q3 INTER –0.34** .020

Note: *p < 0.05; **p < 0.01.

While other independents variables Q1, Q2, Q3 and Q5 are not statistically significant in the model with TERM as dependent variable, the control variable such as age of the organisation (A3), size of the organisation (A5) as well as the other dependent variables such as nationality (A8) of the partner and the type of the relationship (A9) were correlated to TERM (see bivariate correlation in Table 4).

8 Discussion and conclusions

In order to examine the effects of the interaction between a set of variables and the achievement of high strategic relationship quality as well as to avoid or eliminate the probability of relationship failures, correlation analysis, factor analysis and regression analysis were used to identify key-variables. The results indicate that the first and most important quality construct of strategic relationships was partner’s infrastructure (Q5). This finding was fully expected and is consistent with those of, for example, Akdag and Zineldin (2010) and Zineldin (2006). Another key point, was that, as in a successful marriage relationship, the behavioural item scales such as devoting time and energy to sustain the relationship (Q5), frequently discuss new possibilities (Q5), Open and honest behaviour (Q4) were more important than the economical or juridical variables such as


profits, investment or agreements to achieve long term and high quality strategic relationship. Reasons for potential relationship failures are also found in Q5 (ATMOS) and Q4 (INTER). Lack of coordination of administration routines, lack of providing each other with accurate information as well as lack of checking each other’s future plans are most critical factors for failure of the strategic relationship. In this sense, marriage and business are alike. These factors are reflecting shared values and or opportunistic behaviour. Dwyer and Oh (1987) also, focused on the importance of shared values and no opportunistic behaviour to achieve high trust and commitment relationship. These findings are ‘in-sync’ with the situation in the studied strategic alliance types (ALLTYP), are characterised by informal contacts, rather than formal and automated transactions. A situation where a partner adapts to the needs of the other partner was also identified as quite important for achieving high TQSAR.

As shown in Figure 1, the fact that there are many correlations and statistically significant positive relationships between most independent variables and the dependents variables makes it difficult to conclude exactly what mix of independent variables that lead to high TQSAR. It is obvious, however, that they are important for avoiding the termination (divorce) and for creating trust and commitment.

Adaptations and flexibility and common goal settings were identified as the most important PROC (Q2) variables for ALLNTH. But it was not included in the other models. It makes sense that it needs long time to build high trust and commitment to justify the costs and efforts of the adjustments of processes to the needs of the other partner. Most interesting and new finding is that there is no any correlation or statically significance between the nationality of the partner which is reflecting the culture factors (A8) and any of the independent variables. That explains why Chinese and Japanese companies have more successful relationships all over the world. From the data collected, it was not possible to draw this conclusion in the context of Mauritius. This could be explained because Mauritius has not been involved in SA in foreign countries to the same extent as Japan and China. Our interviews showed that different culture should not a barrier for achieving long term relationship. Different cultures provide diversified opportunities. Cultures stress the importance of harmony in relationships as well as in relation to the external environment, which assume that people are basically good and value relationships (Das and Kumar, 2010). One more interesting finding is that the termination of strategic alliance (divorce) is statistically significant with only INTER variables. That is also a logical finding. As in marriage, a cooperative business relationship grows over time as trust and commitment between business partners develop (Zafirovski, 2005; Zineldin, 2002).

The 5Qs model includes different trust and commitment scales. Trust and commitment building process is a social exchange. Social exchange relations evolve in a slow process, starting with minor transactions in which little trust is required because little risk is involved and in which both partners can prove their trustworthiness, enabling them to expand their relations and engage in major transactions (Zineldin, 2000; Blau, 1964).


9 Development and validation of measures

In addition to the substantial findings, this paper contributes to the development and validation of several empirical measures. We believe that our contribution towards the validation of scales is important because it helps build a common framework for conducting research and disseminating results. Parts of the developed and used measures had previously been used in other settings, in other industries and in other countries. Our research shows that the measures should be as general to be used in different contexts.

Although we designed the study to provide reliable and valid measures, it is important to realise that all studies are limited to some extent in terms of generalisability. The results of this study can be replicated using larger sample sizes in order to draw any conclusion.

10 Future research

Our study focused on TQSAR in general and did not focus on how successful or unsuccessful relationships were or in which sector or country the relationship was better or worse. The underlying variables that make a relationship successful are likely to be more or less important in various contexts such as well-developed or less developed partnership. Empirical research showed that the relationships between underlying variables and various contexts would improve the understanding of how to create sustain and/or avoid failures of relationships in various sectors, countries and environments.

Acknowledgements

The correspondent author is grateful for the financial support provided by Linnaeus University and valuable comments received from Mark Slade President of DHL in Tokyo and Steve Mushero, CEO of China NetCloud in Shanghai during the personal interviews.

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