Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms “method” and “method bias” and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

Sources of Method Bias in Social Science Research and Recommendations on How to Control It

计量经济分析 = Econometric analysis

A separate and distinct interaction with both the actual e-vendor and with its IT Web site interface is at the heart of online shopping Previous research has established, accordingly, that online purchase intentions are the product of both consumer assessments of the IT itself-specifically its perceived usefulness and ease-of-use (TAM)-and trust in the e-vendor But these perspectives have been examined independently by IS researchers Integrating these two perspectives and examining the factors that build online trust in an environment that lacks the typical human interaction that often leads to trust in other circumstances advances our understanding of these constructs and their linkages to behavior

Our research on experienced repeat online shoppers shows that consumer trust is as important to online commerce as the widely accepted TAM use-antecedents, perceived usefulness and perceived ease of use Together these variable sets explain a considerable proportion of variance in intended behavior The study also provides evidence that online trust is built through (1) a belief that the vendor has nothing to gain by cheating, (2) a belief that there are safety mechanisms built into the Web site, and (3) by having a typical interface, (4) one that is, moreover, easy to use

Trust and TAM in online shopping: an integrated model

The authors integrate theory developed in several disciplines to determine five cognitive processes through which industrial buyers can develop trust of a supplier firm and its salesperson. These p...

An Examination of the Nature of Trust in Buyer–Seller Relationships:

This paper aims to predict consumer acceptance of e-commerce by proposing a set of key drivers for engaging consumers in on-line transactions. The primary constructs for capturing consumer acceptance of e-commerce are intention to transact and on-line transaction behavior. Following the theory of reasoned action (TRA) as applied to a technology-driven environment, technology acceptance model (TAM) variables (perceived usefulness and ease of use) are posited as key drivers of e-commerce acceptance. The practical utility of TAM stems from the fact that e-commerce is technology-driven. The proposed model integrates trust and perceived risk, which are incorporated given the implicit uncertainty of the e-commerce environment. The proposed integration of the hypothesized independent variables is justified by placing all the variables under the nomological TRA structure and proposing their interrelationships. The resulting research model is tested using data from two empirical studies. The first, exploratory study comprises three experiential scenarios with 103 students. The second, confirmatory study uses a sample of 155 on-line consumers. Both studies strongly support the e-commerce acceptance model by validating the proposed hypotheses. The paper discusses the implications for e-commerce theory, research, and practice, and makes several suggestions for future research.

Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model

Marketing managers must know the time orientation of a customer to select and use marketing tools that correspond to the time horizons of the customer. Insufficient understanding of a customer's ti...

https://www.jstor.org/stable/pdfplus/1252265.pdf

Determinants of Long-Term Orientation in Buyer-Seller Relationships:

Powerful suppliers often require retailers to make significant idiosyncratic investments to improve coordination between organizations and to enhance the supplier’s presence in the end market. The authors examine how a retailer might better manage the hold-up potential of these transaction-specific investments (TSIs) through the use of three control mechanisms: supplier’s TSIs, the development of relational norms, and the use of explicit contracts. Moreover, the authors consider the time-dependent nature of these mechanisms by observing their effects on commitment over the course of a relationship life cycle. The results indicate that (1) a retailer’s TSIs have a negative effect on its perceptions of supplier commitment; (2) a supplier’s TSIs and relational norms increase the retailer’s perception of supplier commitment, whereas explicit contracts are associated with perceptions of lower supplier commitment; and (3) each of the three control mechanisms moderates the negative impact of retailer in...

Control Mechanisms and the Relationship Life Cycle: Implications for Safeguarding Specific Investments and Developing Commitment:

This research investigated how customers' relationships with a service organization affect their reactions to service failure and recovery. Our conceptual model proposed that customer-organizational relationships help to shape customers' attributions and expectations when service failures occur. The empirical results showed that customers with higher expectations of relationship continuity had lower service recovery expectations after a service failure and also attributed that failure to a less stable cause. Both the lower recovery expectations and the lower stability attributions were associated with greater satisfaction with the service performance after the recovery. These effects appeared to be key processes by which relationships buffer service organizations when service failures occur.

Service failure and recovery: The impact of relationship factors on customer satisfaction

Marketing academics and practitioners frequently employ cross-sectional surveys. In recent years, editors, reviewers, and authors have expressed increasing concern about the validity of this approach. These validity concerns center on reducing common method variance bias and enhancing causal inferences. Longitudinal data collection is commonly offered as a solution to these problems. In this article, the authors conceptually examine the role of longitudinal surveys in addressing these validity concerns. Then, they provide an illustrative comparison of the validity of cross-sectional versus longitudinal surveys using two data sets and a Monte Carlo simulation. The conceptualization and findings suggest that under certain conditions, the results from cross-sectional data exhibit validity comparable to the results obtained from longitudinal data. This article concludes by offering a set of guidelines to assist researchers in deciding whether to employ a longitudinal survey approach.

Cross-Sectional Versus Longitudinal Survey Research: Concepts, Findings and Guidelines

Previous research has found that trust is positively related to commitment in buyer-seller relationships. However, the validity of this finding is questionable because trust has been operationalized in many different ways. For example, prior research has not distinguished among levels of trust (interpersonal or organizational trust) and dimensions or motives of trust (credibility or benevolence). In this study, we distinguish among the levels and dimensions of trust. The results indicate that trust in a sales representative (interpersonal credibility) is more strongly related to commitment than trust in an organization (organizational credibility). In contrast, trust based on organizational benevolence is a stronger predictor of commitment than interpersonal benevolence.

Shankar Ganesan

Papers

Determinants of Long-Term Orientation in Buyer-Seller Relationships:

Control Mechanisms and the Relationship Life Cycle: Implications for Safeguarding Specific Investments and Developing Commitment:

Service failure and recovery: The impact of relationship factors on customer satisfaction

Cross-Sectional Versus Longitudinal Survey Research: Concepts, Findings and Guidelines

Dimensions and Levels of Trust: Implications for Commitment to a Relationship