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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.

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.

The purpose of this paper is to examine the cost/benefit (C/B) analysis of four configurations for a repairable system with two primary components/units and one standby.

The four configurations are set to the status of the detection and switching failure of standby, as well as the possible reboot of failed units. The time to failure for each of the primary and standby is assumed to follow an exponential distribution. The time to repair and the time to reboot is assumed to have a k‐stage Erlang distribution. The paper develops the explicit expressions of the mean time to failure (or MTTF) and the steady‐state availability (or A) for four various configurations and performed some comparative analysis. Based on the C/B criterion, comparisons are made for specific values of distribution parameters and of the costs of the units. The four various configurations for a repairable system are ranked by using MTTF, A and C/B, where B is either MTTF or A.

Although it is uncertain which configuration is the optimal one among the four ones, the paper provides much comparative information to manager and manufacturers. Managers can use these results to choose the best configuration according to the used data of parameters and selections of the weight of MTTF or Cost/MTTF.

This paper shows a comparative analysis for a two‐unit online repairable system with one standby under four different configurations. It is the first discussion of comparable work on reliability and availability models for redundant repairable systems in which the units are characterized by detection, switching failure and reboot.

This research was aimed at investigating the fire performance of LSF wall systems by using 3-D heat transfer FE models of existing LSF wall system configurations.

This research was focused on investigating the fire performance of LSF wall systems by using 3-D heat transfer finite element models of existing LSF wall system configurations. The analysis results were validated by using the available fire test results of five different LSF wall configurations.

The validated finite element models were used to conduct a parametric study on a range of non-load bearing and load bearing LSF wall configurations to predict their fire resistance levels (FRLs) for varying load ratios.

Fire performance of LSF wall systems with different configurations can be understood by performing full-scale fire tests. However, these full-scale fire tests are time consuming, labour intensive and expensive. On the other hand, finite element analysis (FEA) provides a simple method of investigating the fire performance of LSF wall systems to understand their thermal-mechanical behaviour. Recent numerical research studies have focused on investigating the fire performances of LSF wall systems by using finite element (FE) models. Most of these FE models were developed based on 2-D FE platform capable of performing either heat transfer or structural analysis separately. Therefore, this paper presents the details of a 3-D FEA methodology to develop the capabilities to perform fully-coupled thermal-mechanical analyses of LSF walls exposed to fire in future.

A transportation connectivity strategy is a crucial part of an adaptive, congruent and sustainable tourism transportation system and is of concern to countries focusing on growing their tourism economy. This study aims to gain a better understanding of the relationship between transportation connectivity and the tourism economy through a configuration analysis.

This study uses fuzzy-set qualitative comparative analysis on a sample of 153 cities in China to provide an understanding of the impacts of transportation connectivity strategies, with the co-effecting factors of socio-economic status, tourism resource endowment and hospitality capacity, on the development of regional tourism economies.

There are multiple paths that lead to regional tourism economic development (a high level of tourist arrivals or a high level of tourism revenue). High-speed rail can play a supportive role, while air travel or traditional rail remains central to the tourism economy. Socio-economic status (i.e. city size and city gross domestic product) and hospitality capacity are identified as crucial influencers for the development of the tourism economy.

This study confirms the validity of deploying configuration analysis (based on the equifinality theory) to establish the relationship between transportation and the tourism economy. The finding of more than one configuration led to a new consensus on how multiple factors influence the tourism economy.

Suggestions on transportation connectivity strategies for different regions are provided.

This study demonstrates the need to place greater emphasis on configurations that lead to tourism economy development instead of the effect of a single transportation mode.

摘要

交通连接策略, 作为打造具备适应性、一致性、可持续性的旅游交通系统的重要环节, 被重视旅游经济增长的国家密切关注。组态分析有助于更好地理解交通连接与旅游经济之间的关系。

本研究以中国的153个城市为样本, 使用模糊集定性比较分析方法（fsQCA）, 研究交通连接策略、社会经济水平、旅游资源禀赋、酒店接待能力等协同因素对区域旅游经济发展的影响。

有多种组态可以导致区域旅游经济的发展（表现为高水平的游客人数或高水平的旅游收入）。航空旅行或传统铁路仍然是影响旅游经济发展的核心条件, 而高铁可以发挥支持作用。社会经济水平(即城市规模和城市生产总值)和酒店接待能力被认为是影响旅游经济发展的关键因素。

本研究证实了应用组态分析（基于等效性理论）建立交通连接策略与旅游经济之间关系的有效性。不唯一的多组态的发现会推动关于多种因素如何影响旅游经济的新共识形成。

本研究针对不同地区提出交通连通策略的建议。

本研究表明, 比起考虑单一交通方式产生的影响, 探索旅游经济发展需要更加重视多种交通连接策略的配置。

Abstracto

Una estrategia de conectividad del transporte es una parte crucial de un sistema de transporte turístico adaptable, congruente y sostenible, y es de interés para los países que se centran en el crecimiento de su economía turística. Un análisis de la configuración puede ayudar a comprender mejor la relación entre la conectividad del transporte y la economía del turismo.

Este estudio utiliza el análisis comparativo cualitativo de conjuntos difusos (fsQCA) en una muestra de 153 ciudades de China para proporcionar una comprensión de los impactos de las estrategias de conectividad del transporte, con los factores coadyuvantes de la situación socioeconómica, la dotación de recursos turísticos y la capacidad de hospitalidad, en el desarrollo de las economías turísticas regionales.

Existen múltiples vías que conducen al desarrollo económico del turismo regional (un alto nivel de llegadas de turistas o un alto nivel de ingresos por turismo). El ferrocarril de alta velocidad puede desempeñar un papel de apoyo, mientras que el transporte aéreo o el ferrocarril tradicional siguen siendo fundamentales para la economía turística. El estatus socioeconómico (es decir, el tamaño de la ciudad y el PIB de la ciudad) y la capacidad de hospitalidad se identifican como factores de influencia cruciales para el desarrollo de la economía del turismo.

Este estudio confirma la validez de utilizar el análisis de configuración (basado en la teoría de la equifinalidad) para establecer la relación entre el transporte y la economía del turismo. El hallazgo de más de una configuración condujo a un nuevo consenso sobre cómo influyen los múltiples factores en la economía del turismo.

Se proporciona una tipología de estrategias de conectividad del transporte para diferentes regiones.

Este estudio demuestra la necesidad de poner mayor énfasis en las configuraciones que conducen al desarrollo de la economía turística en lugar del efecto de un único modo de transporte.

As purveyors of knowledge-based and high value-added services to the manufacturing sector, industrial service small- and medium-sized enterprises (SMEs) must develop the information technology (IT) capabilities that, in combination with other non-IT capabilities, enable their capacity for organizational learning (OL) and for explorative learning in particular. In this context, this study aims to identify the different causal configurations that account for the nonlinear complex interplay of IT capabilities for exploration and strategic capabilities for explorative learning as they affect these firms’ competitive performance.

Survey data obtained from 92 industrial service SMEs were analyzed with a configurational approach, using fuzzy set qualitative comparative analysis (fsQCA).

As it allows for equifinality, the fsQCA analysis identified two sets of causal configurations that characterize the sampled firms’ explorative learning capability as it relates to competitive performance. In the first set, two configurations were equally associated with high innovation performance, whereas in the second set, four configurations were equally associated with high productivity.

By viewing explorative learning as a dynamic capability that is enabled by the firm’s IT and strategic capabilities, the study contributes to OL theory by providing a more concrete or “operational” grounding, which allows for a greater practical applicability of this theory. By taking both the configurational and capability-based views of the OL-IT-performance causal framework, the authors provide an empirical basis for unraveling, explaining and understanding the complex non-linear relationships embedded within this framework.

Through examining the two constructs of inter-organizational complementarity and inter-organizational compatibility in supply chains, the purpose of this paper is to develop a taxonomy of focal firms’ inter-organizational fit (IOF) configurations with their suppliers and customers, and examine the relationship between these configurations and environmental innovation (EI) in order to answer the question of “with whom” to collaborate for EI development.

A survey instrument was elaborated and data from a sample of 171 US firms were collected. The authors adopted cluster analysis to identify the IOF taxonomy. Canonical discriminant analysis was employed to uncover underlying dimensions between clustering variables and cluster membership. Then, ANOVA tests were conducted to investigate relationships between IOF configurations in the context of EI in supply chains.

Three configurations were identified based on the complementarity and compatibility between focal firms and their supply chain partners. It is observed that the overall IOF level is positively related to firms’ EI outcomes. Moreover, inter-organizational complementarity facilitates incremental EI while inter-organizational compatibility plays a more crucial role in radical EI. Both are required to achieve the best innovation outcome.

This research develops the first taxonomy for depicting IOF in a supply chain innovation context and also clarifies different rationale behind the development of incremental and radical EI through examining distinctive effects of the complementarity and compatibility with supply chain partners.

Given the complexity of building information modeling (BIM) adoption decisions in small- and medium-sized enterprises (SMEs) in the Architecture, Engineering and Construction (AEC) industry, understanding BIM adoption decision-making through the net effect of a single factor on BIM adoption decisions alone is limited. Therefore, this paper analyzed the co-movement effect of managers' psychological factors on the BIM adoption decisions from the perspective of managers' perceptions. The purpose is to let managers have a deep understanding of their BIM adoption decisions, and put forward targeted suggestions for the AEC industry to promote the adoption of BIM by SMEs.

Data from 192 managers in SMEs collected by the questionnaire were used in a fuzzy set qualitative comparative analysis (fsQCA). Due to the limitations of fsQCA in making the best use of the data used, as a complement to fsQCA, necessary conditions analysis (NCA) was used to analyze the extent to which necessary conditions influenced the outcome.

(1) NCA analysis shows that high perceived resource availability (PRA) and high performance expectancy (PE) are necessary conditions for high BIM adoption intention (AI). (2) fsQCA analysis shows that high PE is the single core condition for high AI. fsQCA analysis identifies three configurations of managers' psychological factors, reflecting three types of managers' decision preferences, namely benefit preference, loss aversion and risk avoidance, respectively. Different decision preferences may lead to different BIM adoption strategies, such as full in-house use, partial in-house/outsourcing and full outsourcing of BIM processes. (3) High perceived risk (PR) and low perceived business value of BIM (PBV) are the core conditions for low AI.

This paper expands on the application of fsQCA to context of BIM adoption decisions. Based on the results of fsQCA analysis, this paper also establishes the relationship between managers' decision-making psychology and BIM adoption strategy choice and analyzes the impact of different decision biases on BIM adoption strategy choice. It concludes with suggestions for encouraging managers to adopt BIM and for avoiding decision-making bias.