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This paper aims to explore the determinants of perceived internal service complexity in internal service encounters. In this context, the nature of internal service complexity is considered, to identify its promoting and limiting factors, as well as its non-linear effects on internal service quality.

To acquire information on factors influencing internal service complexity, a broad literature review was conducted. Furthermore, to validate and verify these results, structural equation modeling’ was used in the context of a quantitative study with 705 internal customers.

The results revealed four promoting and seven limiting complexity determinants at organizational, interdepartmental and internal supplier-related levels. Moreover, the findings showed that an optimal, moderate level of internal service complexity maximizes internal service quality.

As the findings are restricted to this study, further research should be conducted with regard to different types of companies and internal customers. Furthermore, future research should take variability over time into account. Executing a longitudinal approach to internal service complexity might therefore be appropriate.

Managers should note that exclusively reducing internal service complexity is insufficient; rather, a hybrid strategy of lowering and controlling is indispensable for an optimization. Based on the identified complexity determinants, a three-step guidance to optimize internal service is proposed.

Despite examining the construct complexity, previous research has neither analyzed internal service complexity nor studied its determinants. This paper provides an empirical model that analyzes inhibiting and promoting factors of internal service complexity as well as its non-linear effects on internal service quality.

Improving the performance of health care organizations is now perceived as essential in order to better address the needs of the populations and respect their ability to pay for the services. There is no consensus on what is performance. It is increasingly considered as the optimal execution of four functions that every organization must achieve in order to survive and develop: reach goals; adapt to its environment; produce goods or services and maintain values; and a satisfying organizational climate. There is also no consensus on strategies to improve this performance. The paper aims to discuss these issues.

This paper intends to analyze the performance of primary health care organizations from the perspective of Kauffman’s model. It mainly aims to understand the often contradictory, paradoxical and unexpected results that emerge from studies on this topic.

To do so, the first section briefly presents Kauffman’s model and lays forward its principal components. The second section presents three studies on the performance of primary organizations and brings out the contradictory, paradoxical and unexpected results they obtained. The third section explains these results in the light of Kauffman’s model.

Kauffman’s model helps give meaning to the results of researches on performance of primary health care organizations that were qualified as paradoxical or unexpected. The performance of primary health care organizations then cannot be understood by only taking into account the characteristics of these organizations. The complexity of the environments in which they operate must simultaneously be taken into account. This paper brings original development of an integrated view of the performance of organizations, their own characteristics and those of the local environment in which they operated.

Based on a conceptual framework of the linkages between strategic manufacturing goals and complexity, the purpose of this paper is to investigate adaptation processes in manufacturing firms to increasing external complexity.

Hypotheses are tested with statistical analyses (group comparisons and structural equation models) that are conducted with data from the third round of the International Manufacturing Strategy Survey.

The study shows that manufacturing firms face different degrees of complexity. Firms in a more complex environment tend to possess a more complex internal structure, as indicated by process configuration, than firms in a less complex environment. Also depending on the degree of complexity, different processes of adaptation to increases in external complexity are initiated by organisations.

Research studies taking into account the dynamics of adaptation processes would be helpful in order to draw further conclusions, for instance, based on longitudinal analyses or simulation studies.

Depending on the level of complexity a firm has been confronted with in the past, different adaptation processes to further growing complexity can be initiated. Firms in high complexity environments have to re‐configure their strategic goals; firms in low complexity environments have to build‐up internal complexity to cope with demands from the outside.

The paper distinguishes between adaptation processes in low and high complexity environments and provides explanations for the differences.

The purpose of our study is to investigate how a manufacturing plant’s internal operations along with its network of connections (upstream and downstream) can have an impact on its recovery time from a disruption. The authors also examine the inverse-U impact of complexity. Finally, the authors test the moderating role that business continuity management plans (BCP) at the plant level have on recovery time.

To test our hypotheses, the authors partnered with Resilinc Corporation, a Silicon Valley-based provider of supply chain risk management solutions to identify focal firms’ suppliers, customers and plant-level data including information on parts, manufacturing activities, bill of materials, alternate sites and formal business continuity plans. The authors employed censored data regression technique (Tobit).

Several important findings reveal that the plant’s internal operations and network connections impact recovery time. Specifically, the number of parts manufactured at the plant as well as the number of internal plant processes significantly increase disruption recovery time. In addition, the number of supply chains (upstream and downstream) involving the plant as well as the echelon distance of the plant from its original equipment manufacturer significantly increase recovery time. The authors also find that there exists an inverted-U relationship between complexity and recovery time. Finally, the authors find partial support that BCP will have a negative moderating effect between complexity and recovery time.

This research highlights gaps in the literature related to supply chain disruption and recovery. There is a need for more accurate methods to measure recovery time, more research on recovery at the supply chain site level and further analysis of the impact of supply chain complexity on recovery time.

Managing organizations in complex environments is a major challenge. Complexity is not only due to the external environment (market and/or technological turbulence) but also to the internal configuration and specificities. A recent stream of studies in organizational literature suggested that organizations should develop and deploy specific capabilities for facing complexity, namely dynamic capabilities. This means becoming more flexible. The paper aims to discuss these issues.

This paper proposes four main capabilities to face four dimensions of complexity. It then investigates if it is more appropriate to focus on a specific capability when facing higher levels of a specific dimension of complexity. The research methodology is a multiple case study in seven different organizational units of the same super-store corporate.

Data showed some important results. First of all, internal complexity is unit specific rather than corporate or industry specific. Moreover, it can derive not only from unpredictability and rate of change, but also from variety of elements and their interactions. All these elements form complexity. Internal complexity is characterized by four main elements: uncertainty, dynamicity, diversity and interdependence. Finally, for each of these elements, different organizational strategies are used: in case of uncertainty, for example, a strategy used by the companies is the sharing of information and the development of redundancy.

Originality lies in linking different capabilities with different dimensions of internal complexity.

Corporate governance scholars have long been interested in understanding the impact of former chief executive officers (CEOs) who do not fully leave office but rather remain as board members. Departing from the inconclusive findings of retaining Janus-faced predecessor CEOs on boards, this study revisits the concept of retaining predecessor CEOs on boards (RPCB) and its influence on successors and firm performance under certain conditions.

The study analyzes a sample of 461 Taiwanese firms from 2015 to 2019, adopting the ordinary least squares regression method to examine the correlation between RPCB and firm performance. It specifically analyzes the moderating effects of the complexity of firms' internal and external environments in this context.

The empirical results show that there is no direct relationship between RPCB and post-succession performance, indicating that this association is shaped by contextual factors. Indeed, the influence of predecessors is more pronounced in situations of high internal and external complexities such that the value of RPCB is situation specific.

This study is the first to generate the resource-based view theory to recognize that the relationship between predecessors on boards and financial consequences is moderated by contextual factors. The authors are the first to extend extant research by considering internal and external complexity in the context of succession and RPCB. In such situations, successors' need for regular mentoring is heightened and the benefits of prior CEO knowledge and resources are more substantial.

In the wake of severe socio-economic damage, many firms have made creative and technological progress in their responses to the COVID-19 crisis. This paper examines internal and external environmental complexity elements as antecedents of business responses and builds a framework for tourism firms to respond to the pandemic crisis.

This study obtained survey data from 395 respondents in the Vietnamese tourism and hospitality industry. A partial least squares structural equation modeling–artificial neural network approach was used to examine various combinations of internal and external environmental complexity elements that have different impacts on business responses and firms' performance.

The knowledge and practice created by the firm's employees (individual creativity), obtained from traditional contexts (traditionality) were identified as internal environmental complexity factors while practice learned from other firms (mimetic pressure), information processing (status certainty) and digital transformation (digital technology speed) were treated as external environmental complexity factors. Internal and external environmental complexity factors influence business responses and firms' performance positively but differently.

This study demonstrates that firms should integrate their internal environment of creativity and traditionality with external environmental factors of mimetic pressure, status certainty and digital technology speed to create better business responses, and thus firm performance in the COVID-19 era.

This investigation contributes to environmental research and narrows the existing research gap relating to the association between types of environmental complexity and firms' responsive action, which then influence firms' performance in terms of sustainable competitiveness.

The importance of the supply network to firm performance is well documented. Until now, the firm and its suppliers have been conceptualized as single entities. Yet, multinational corporations (MNCs) are composed of a complex, geographically dispersed internal network of subsidiaries. The supply and internal networks are inherently linked. The purpose of this study is to investigate the impact of the interaction of these networks on firm-level financial performance.

Building on supply network, internal network and dual embeddedness research, the authors investigate the interaction of these networks using supply network data from FactSet and internal network data from Orbis. We assess the impact at the MNC level, using measures of firm-level financial performance, physical proximity between the two networks and geographic dispersion of the internal network.

The results show that the performance effect of physical proximity of the firm with its supply network is negatively moderated by the geographic dispersion of the firm's internal network. This effect can be traced back to the diminishing marginal profitability of a firm's assets. Moreover, the benefits of dual embeddedness to the individual subsidiary come at a cost at the firm-level due to the operational challenges of managing a complex subsidiary network.

This study is the first to investigate the supply and internal networks of MNCs simultaneously.

The paper extends supply network literature by considering the internal network of the focal firm and its suppliers. This paper is one of the first studies that offer an understanding of the interaction between supply and internal networks of a focal firm and the effect on financial performance.

This study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.

Fuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.

Drawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.

This study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.

This study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

The purpose of this paper is to integrate process complexity as an object of analysis within effective quality management (QM).

This paper systematically analyzes different conceptions of complexity theory and characterizes process complexity from a QM perspective producing new insights how to address process complexity for continuous improvement.

The authors identified and specified four complexity characteristics, which we integrated in a holistic process complexity model (PCM). The author further developed the idea of internal and external process complexity and demonstrated that internal complexity needs to balance external complexity. Based on the PCM, internal process complexity can be analyzed and suitable management approaches can be selected, while conventional QM practices showed to be inefficient or even contra-productive when applied in the context of process complexity.

This research is adapted to fit the needs of production processes. The PCM is designed from a QM perspective.

The developed model allows companies to specify and characterize process complexity in order to reflect on the appropriateness of their process management approaches. Furthermore, it gives an additional perspective on process analysis for tapping the full potential of process improvement programs.

This paper combines complexity theory with QM.