ABSTRACT

Purpose: The purpose of this paper is to explore whether dyadic operationalization within business relationships is feasible and sensible in a rigorous way. It aims to introduce quantitative operationalizations of business relationship characteristics from both monadic and dyadic datasets, and to introduce aggregation techniques for utilizing the richness of dyadic data. It compares and contrasts the effectiveness of different techniques in terms of explaining business relationship phenomena, using an empirical exemplification.

Methodology/Approach: The paper reviews the relevant literature and summarizes various dyadic operationalization and aggregation approaches. It furthermore illustrates such operationalization and aggregation by utilizing an empirical example. A nomological model of marketing-purchasing collaboration is developed and tested based upon internal dyadic data. Using alternative model comparisons, we contrast several different ways of operationalizing dyadic data (combined, dyadic, and dyadic with asymmetry), and compare the outcomes utilizing structural equation modeling.

Findings: The study of business relationships typically makes use of a variety of data types, ranging from simple monadic to perceived dyadic, through to rigorous dyadic data. The various aggregation methods include value, asymmetry, and directional asymmetry approaches. Pertinent sub-constructs are developed based on these aggregation methods and relevant hypotheses incorporating and reflecting on the role of the sub-constructs are suggested to develop a more meaningful and rich quantitative analysis of business relationship phenomena.

Research Implications: This paper explores the different ways in which data assessing the relationship between two interacting parties can be operationalized. Dyadic operationalization within the context of business relationships is sensible and recommended. Researchers can adopt approaches to conduct dyadic data operationalization including data collection methods such as perceived dyadic and rigorous dyadic. They should benefit from rich dyadic aggregation approaches such as value, asymmetry, and directional asymmetry, noting the strengths and weaknesses of each approach discussed in this paper.

Practical Implications: Businesses are recommended to increase customer orientation and marketing-purchasing interaction to improve collaboration between marketing and purchasing departments and thus their overall performance. Businesses should also develop an alignment between the collaboration perceptions of the involved departments, and note that perceptual symmetry improves collaboration. Perception matching in a dyadic relationship plays a role in enhancing the overall firm performance. Managers should note that all involved parties’ perspectives are to be included to ensure a positive and collaborative liaison. An all-encompassing attitude and perspective (as opposed to an asymmetric, unbalanced one) ensures an effective relationship.

Originality/Value/Contribution of the paper: The contribution of the research lies in outlining different ways to accomplish more insightful analytics regarding data operationalization, and their different strengths and weaknesses in terms of explaining relationship characteristics, and therefore enriches research on business relationships by making better sense of quantitative dyadic data.

摘要

目的：本文的目的是探索严格的方式在业务关系中进行二元化操作是否可行和明智。它旨在介绍来自单子数据集和二元数据集的业务关系特征的定量可操作化，并介绍利用二元数据丰富性的聚合技术。它使用经验例证在解释业务关系现象方面比较和对比了不同技术的有效性。

方法论/方法：本文回顾了相关文献并总结了各种二元化操作和聚合方法。此外，它通过经验示例来说明这种操作和聚合。基于内部二元数据，开发并测试了营销与购买合作的经济学模型。使用替代模型比较，我们对比了几种不同的二元数据操作方式（组合，二元和不对称二元数据），并利用结构方程模型比较了结果。

结果：对业务关系的研究通常利用各种数据类型，从简单的单子数据到感知到的二进数据，再到严格的二进数据。各种聚合方法包括值，不对称和方向不对称方法。基于这些汇总方法开发了相关的子结构，并建议了结合并反映子结构作用的相关假设，以对业务关系现象进行更有意义和更丰富的定量分析。

研究意义：本文探讨了可用于操作评估两个交互方之间关系的数据的不同方式。在业务关系范围内进行二元化操作是明智的，建议这样做。研究人员可以采用进行二元数据操作的方法，包括诸如感知二元和严格二元数据之类的数据收集方法。他们应该受益于丰富的二元聚合方法，例如值，不对称性和方向性不对称性，并注意到本文讨论的每种方法的优缺点。

实际影响：建议企业增加客户导向和营销与采购互动，以改善营销和采购部门之间的协作，从而改善整体绩效。企业还应该在相关部门的协作感知之间建立一致，并注意感知对称可以改善协作。亲密关系中的知觉匹配在提高公司整体绩效中发挥了作用。管理人员应注意，应包括所有相关方的观点，以确保积极和协作的联系。包罗万象的态度和观点（与不对称，不平衡的观点相对）确保了有效的关系。

本文的独创性/价值/贡献：本研究的贡献在于，概述了有关数据操作化的更深入分析的不同方法，以及在解释关系特征方面的不同优缺点，因此通过使对定量二进数据有更好的了解。