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The aim of this study is to examine how the technological heterogeneity of suppliers affects the performance of the focal firm. The analysis of this issue is particularly relevant in the current period, which is characterized by rapid and often radical technological innovations that play an increasingly important role in the competitiveness of firms. The authors examine this central impact in two dimensions: the short-term effect on performance is evaluated using the well-known indicators of business performance, while the long-term effect is studied through the concept of dynamic capability. As previous works report contradictory results on the performance consequences of diverse business relationships, the authors also investigate the underlying factors influencing these impact mechanisms. Their theoretical model is tested using a structural equations method on a sample of Hungarian firms, including the mediating effect of the customer's efforts to improve its supply chain management and the moderating effect of its network capability. The results show that the technological heterogeneity of suppliers indirectly affects both the actual business performance and the R&D capability of the customer firm through its supply chain management's efforts. Meanwhile, the analysis of the moderating factor clearly demonstrates that the advanced network capability of the customer firm is a prerequisite for the positive performance effect of a heterogeneous supplier portfolio. [ABSTRACT FROM AUTHOR]

The paper presents and empirically tests a special repetitive trust game. The game distinguishes three trust-related terms: trust, trustworthiness, and reliability. Both trust and trustworthiness are interpreted as a flow type of concepts that can be captured and investigated through the specific movements and actions made by the partners in the game. Reliability is conceptualized as a stock type phenomenon and reflects the perceived level of the trustor toward his/her partner, the trustee. The authors’ special repetitive trust game consists of ten iterations. Anonymous pairs are created, and the perceived level of reliability is directly measured through 10 rounds of the game. The game is also featured by its cumulative character. It means that through the 10 rounds, the amount of the previous iterations can be reinvested. This game design is used for testing the core hypothesis: the actions of the partners of a pair in the game - and the related level of trust and trustworthiness (flow concepts) - depend on the perceived levels of reliability (stock). [ABSTRACT FROM AUTHOR]

The aim of the paper is to examine the mathematical statistics foundations of dyadic data analysis. In a former study, it was investigated whether the dyadic data analysis significantly contributes to traditional statistical analysis and provides surplus in understanding statistical phenomenon, or not. Further, the authors try to correct some of the mathematical structures of dyadic data analysis. The theoretical critics are supplemented by empirical tests. [ABSTRACT FROM AUTHOR]

The study of business relationships poses a number of challenges. This article focuses specifically on the methodological issues arising from the dyadic nature of relations. As a consequence of the dyadic nature, it is important that throughout the analyses the phenomena can be measured as embedded in the given relation and in this way, they can be studied without losing their unique context. A common criticism of using questionnaire surveys in examining business relations is that in research, the so-called single-ended operationalising or measure is dominant, and the data thus obtained is analysed by traditional mathematical-statistical methods. According to critical opinions in the literature, this methodological practice cannot lead to reliable results. The present article uses the database of a questionnaire survey to investigate whether the former standpoint is well founded. A specific research hypothesis is tested on the data obtained from paired query. In this process, the suggested methods for dyadic data analysis are used besides analyses carried out using various measures from traditional statistics. Dyadic data analysis provides extra value primarily in its perspective; regarding the results in the present study, it has not proved to be a major breakthrough. [ABSTRACT FROM AUTHOR]

The paper focuses on the methodological challenges of a state-of-the-art survey-based business research related to trust and to other relevant attributes. Reviewing the literature of the subject, the authors explore the current methodological solutions for dyadic business phenomena. These solutions, however, ignore the differences in perceptions that exist between counterparts of concrete relationships. Consequently, they are not suitable to analyze dependencies in such relationships, especially not the problem of mutuality. Theoretically, these limitations can be overcome by pairwise sampling and dyadic data analysis. In the present study, the following hypothesis is tested based on a survey sample built on pairwise sampling: In a business relationship characterized by mutually perceived trustworthiness of high level, the willingness to be involved in a risky situation is greater than in relationships where actors do not believe that their partners are highly trustworthy. To test this theory, not only the two solutions suggested by dyadic data analysis but also traditional mathematical-statistical techniques are applied. Although the literature suggests that the latter has severe limitations, the results of the authors do not show significant differences. [ABSTRACT FROM AUTHOR]

The paper focuses on the methodological challenges of a state-of-the-art survey-based business research related to trust and to other relevant attributes. Reviewing the literature of the subject, the authors explore the current methodological solutions for dyadic business phenomena. These solutions, however, ignore the differences in perceptions that exist between counterparts of concrete relationships. Consequently, they are not suitable to analyze dependencies in such relationships, especially not the problem of mutuality. Theoretically, these limitations can be overcome by pairwise sampling and dyadic data analysis. In the present study, the following hypothesis is tested based on a survey sample built on pairwise sampling: In a business relationship characterized by mutually perceived trustworthiness of high level, the willingness to be involved in a risky situation is greater than in relationships where actors do not believe that their partners are highly trustworthy. To test this theory, not only the two solutions suggested by dyadic data analysis but also traditional mathematical-statistical techniques are applied. Although the literature suggests that the latter has severe limitations, the results of the authors do not show significant differences. [ABSTRACT FROM AUTHOR]