Search results

This study explores the configurations of management control systems (MCSs) while taking into account entrepreneurial cognition styles (ECSs) in small and medium enterprises (SMEs). The objective is to understand the impact of ECS on deployment and identify the various modes of MCS configurations employed by SMEs. The authors draw on and synthesise two theoretical perspectives relating to cognition and management control packages to understand the associations between ECS and MCS employed by SMEs in managing their business. This study was conducted using a quantitative approach that utilises a questionnaire survey to collect cross-sectional data from 150 SMEs. The authors uncovered three cognitive styles: knowing (e.g. preciseness), planning (e.g. organising), and creativity (e.g. innovativeness). Furthermore, five configurations of MCS utilised by SMEs were identified: customer focus, performance monitoring, administrative focus, strategic focus, and development focus. By combining both analyses, the authors discovered three constellations of significant association between ECS and MCS characterised by Cluster 1’s cohesive integration approach, Cluster 2’s revealing strategic approach, and Cluster 3’s multifaceted exploration. The study is significant because it uncovers the complex relationship between ECS and MCS configurations, highlighting their interdependence within the institutional context. Using a cognitive view, the authors explore how the cognitive styles of entrepreneurs facilitated imprinting institutional context into MCS configurations. These insights enable us to envisage that ECS is not mutually exclusive but forms a continuum that provides more plausible explanations that relax the direct universal relationship between MCS configurations and contextual factors.

Purpose – Agribusiness is crucial for the Brazilian trade balance surplus. Innovation, not only that focused on technology or productivity, is a basic condition for its development. The context of the agribusiness activities in a developing country is dynamic and requires a multilevel and multifaceted view. This suggests that these features need to be incorporated both in the theories and methods. Therefore, we propose a method, from within the perspective of Configurations Theory, of capturing this dynamic multidimensionality. The method was applied in the context of the rice-farming business in Southern Brazil.

Methodology/approach – The proposed method, which we refer to as a Case Study Method with Multiple Units of Analysis and Mixed Methods, was applied in a research organization in an attempt to identify the evolution of innovation while considering a theoretical perspective based on multilevel rules.

Findings – Six different configurations in the temporal organization of research were identified. These six configurations describe the evolution of four emphases given to innovation, the drivers associated with the evolution of these emphases, and the changes that have occurred over time.

Social implications – The results may provide support for new public policies for rice farming and lead to improvements in the organization's strategies for innovation.

Originality/value of chapter – The combination of methods used (Case Study, Qualitative Comparative Analysis, Social Network Analysis, Path Dependence, and Patterns of Decision Making) to study configurations, together with the dynamic approach to innovation based on multilevel rule, is unique.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions in human resource management (HRM). Since so far empirical evidence on this is, however, lacking, the authors' study examines which combinations of data and analyses are employed and which combinations deliver on the promise of improved decision quality.

Theoretically, the paper employs a neo-configurational approach for founding and conceptualizing HRA. Methodically, based on a sample of German organizations, two varieties (crisp set and multi-value) of qualitative comparative analysis (QCA) are employed to identify combinations of data and analyses sufficient and necessary for HRA success.

The authors' study identifies existing configurations of data and analyses in HRM and uncovers which of these configurations cause improved decision quality. By evidencing that and which combinations of data and analyses conjuncturally cause decision quality, the authors' study provides a first confirmation of HRA success.

Major limitations refer to the cross-sectional and national sample and the usage of subjective measures. Major implications are the suitability of neo-configurational approaches for future research on HRA, while deeper conceptualizing and researching both the characteristics and outcomes of HRA constitutes a core future task.

The authors' paper employs an innovative theoretical-methodical approach to explain and analyze conditions that conjuncturally cause decision quality therewith offering much needed empirical evidence on HRA success.

Qualitative Comparative Analysis (QCA) is a promising, powerful method that is increasingly used for IS research. However, the Information Systems (IS) discipline still lacks a shared understanding of how to conduct and report QCA. This paper introduces the fundamental concepts of QCA, summarizes the status quo, and derives recommendations for future research.

A descriptive literature review in major IS outlets summarizes how and why QCA has been used in the IS discipline, critically evaluates the status quo, and derives recommendations for future QCA studies.

The literature review reveals 32 empirical research articles in major IS journals that have used the QCA method. Articles applied QCA to a broad range of research topics at the individual and organizational levels, mainly as a standalone analysis for theory development, elaboration and testing. The authors also provide evidence that most published IS research articles do not take full advantage of the potential QCA, such as analyzing necessary causal conditions or testing the robustness of QCA results. The authors provide seven actionable recommendations for future IS research using QCA.

The literature review assesses the status quo of QCA’s application in the IS discipline and provides specific recommendations on how IS researchers can leverage the full potential of QCA.

This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.

With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.

The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.

It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.

In organizational research the object of study is often a process, that is, a complex of events and activities that unfolds over time. In this chapter we focus on temporally ordered configurations, which can be defined as those configurations in which conditions occur in a specific temporal order. We illustrate the aims, characteristics, and limitations of several approaches that have been proposed as tools for the analysis of temporal order. Our illustration involves an analysis of the “gestation activities” of nascent entrepreneurs, that is, persons involved in the creation of a new firm. We aim to identify temporal sequences of gestation activities that generate or allow a successful outcome of the gestation process, while an occurrence of the same activities in another temporal order will not generate or allow that outcome. First we discuss Event Structure Analysis and Optimal Matching and conclude that these approaches cannot provide the kind of analysis that we are aiming at in this chapter. Then we discuss Temporal Qualitative Comparative Analysis, for which our analysis points to technical limitations that constrain its application. We then present and discuss an alternative approach, Temporal Necessary Condition Analysis.

This chapter acknowledges the difficulties in the empirical study of social ventures – broadly defined as market-driven ventures that produce social change – that arise from the vast differences among social venture firms in terms of missions, goals, identities, strategies, and structures. In an effort to improve research in this area and advance the field of social entrepreneurship, the authors advocate approaching social ventures from a configurational perspective.

This chapter begins with a discussion of what social ventures are and why organizational configurations – sets of firms that are similar across key characteristics – may be an appropriate perspective to utilize. Then, two methods – cluster analysis and set-theoretic analysis – are discussed in detail as ways to approach the study of social venture configurations. Details include descriptions of the techniques, instructions for use, examples, and limitations for each.

This chapter identifies research opportunities using configurations approaches in social venture research. Substantial possibilities for multilevel and temporally based research are discussed in depth.

A configurational approach can address the incongruence and non-findings in current social venture research and offers new opportunities for future research.

Developing and implementing strategies to maximize profitability is a fundamental challenge facing manufacturers. The complexity of orchestrating resources in practice has been overlooked in the operations field and it is now necessary to go beyond the direct effects of individual resources and uncover different resource configurations that maximize profitability. The paper aims to discuss these issues.

Drawing on a sample of US manufacturing firms, multiple regression analysis (MRA) and fuzzy set qualitative comparative analysis (fsQCA) are performed to examine the effects of resource orchestration on firm profitability over time. By comparing the findings between analyses, the study represents a move away from examining the net effects of resource levers on performance alone.

The findings characterize the resource conditions for manufacturers’ high performance, and also for absence of high performance. Pension and retirement expense is a core resource condition with R&D and SG&A as consistent peripheral conditions for profitability. Moreover, although workforce size was found to have a significant negative effect under MRA, this plays a role in manufacturers’ performance as a peripheral resource condition under fsQCA.

Accounting for different resource deployment configurations, this study deepens knowledge of resource orchestration and presents findings that enable manufacturers to maximize profitability. An empirical contribution is offered by the introduction of a new method for examining manufacturing strategy configurations: fsQCA.

Plant configuration management systems address all phases of the plant’s life cycle, from engineering design, re‐design, maintenance, to operations. However, as yet little research has been reported on plant configuration management information systems analysis. During the past decade, the object‐oriented approach has received much attention in information systems development. This paper describes an object structure for plant configuration management systems analysis. Three major aspects of configuration management (maintenance, re‐design change, and business process) and fundamental types of objects engaged in configuration management are described. The association between these objects is then built through identifying the messages between the objects. Practical application of this framework shows that it is useful for the analysis and design of a plant configuration management information system.