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This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

The purpose of this paper is to analyze the determinants of the performance of regional industrial technology development programs among the regional strategic industrial development program that the central government and Daegu metropolitan city jointly promoted between 2004 and 2012. Specifically, in this research, the authors are trying to identify the effects of R&D capabilities and technical development tasks on technological and managerial performance.

The dependent variables of this study are technical and economic performance. Technical performance, product and process innovation, economic performance, sales and export increases were measured using five-point Likert scales. The authors added the contribution of sales through technology development to economic performance. The independent variable is the company’s R&D capability, measured by the number of R&D staff compared to the average total number of employees from 2004 to 2012. The characteristics of the technology development tasks were measured by technical characteristics, market characteristics and collaborative research types. The technological characteristics were measured by seven factors, including technological change, technical difficulty, potential in commercialization, competition between domestic and foreign competitors, difficulty in introducing overseas technology and the technological gap. Market characteristics were largely divided into complexity, dynamics and competitiveness. The types of collaborative research were divided into whether or not there were collaborative research with the participation of large corporations. The control variables are firm size (number of employees) and firm age. Regression analysis was used to analyze the determinants of performance, and a difference analysis was conducted to determine the effect of collaborative research on performance.

The main determinants of the regional industrial technology development program performance are the characteristics of the technology development task rather than the internal R&D capability; moreover, the technical characteristics, complexity of the developed product market and participation of large corporations had significant effects on R&D capability. The R&D capacity of firms in internal R&D capacity had a significant effect only on the improvement of technology development ability. Therefore, R&D capacity, which is the main determinant of technology innovation, did not have a significant effect on the performance of short-term technology development tasks. Technological change, technological difficulty, competition between domestic and foreign competitors and the technological gap had positive effects on performance, excluding sales contributions. In addition, the complexity of the developed product market such as the diversification of demand, competitive product and sales distribution channels had positive influences on the performance of technology development programs, unlike dynamics and competitiveness. In this study, the authors cannot confirm the effect of collaborative research on the performance of the technology development programs, but they confirmed that collaborative research involving large corporations had a positive influence on performance.

The results of the analysis of the determinants of regional industrial technology development programs suggest some implications in the future evaluation of these regional industrial technology development programs. It is necessary to review the application qualification and merit, advance review of the business plans and confirmation, an examination of the research results and performance of the applicants and a review of the technology and market situation of the project. For this, the authors suggest that the written review from the relevant technical experts be submitted to the evaluation committees. Also, when establishing regional industrial development programs, they should be evaluated thoroughly, including detailed information and contents about the technical and market characteristics of the local industry.

This research is one of the first to investigate the achievements of R&D support programs among regional industrial development programs in Korea. The results of this study can substantially contribute to the development and implementation of the R&D support policies of the central and local governments. Furthermore, the findings suggest guidelines for improving the performance of R&D support programs in the future. A theoretical model for enhancing the efficiency of government R&D support programs may be established, and an empirical analysis may be conducted to provide practical and academic implications for further research.

This study aims to analyse how multinational corporations (MNCs) organise value chain activities to penetrate new market segments. It contributes by expanding traditional decisions regarding the vertical fine-slicing of value chain activities (whether performed internally or externally) and the consideration of resource-sharing decisions (integration or separation) for each value chain function.

The authors draw on primary data collected from two case study firms operating in the large emerging Chinese market: Volvo Construction Equipment AB and Epiroc AB. In-depth cases illustrate how foreign MNCs expand into new market segments and simultaneously target both the lower-priced mid-market and the premium segments in the Chinese mining and construction industry.

The results reveal that product diversification creates challenges for managers who must oversee new (vertical) value chains, often simultaneously. Beyond geography and modes of governance, managers must decide whether to integrate or separate value chain activities for the new product lines. The study identifies four main strategic choices for firms to address this complexity, focusing on the decision to internalise or externalise (i.e. within or across organisational boundaries) and integrate or separate value chain activities between different product lines.

This study builds upon the internalisation theory and recent international business contributions that focus on value chain configurations to explain MNCs’ product diversification as a growth strategy in a host emerging market. It also sheds light on the choice of conducting new activities in-house or externally and elucidates firms’ managerial decisions to operationally integrate or separate individual value chain activities. The study provides insights into the drivers explaining managerial decisions to configure value chain activities across product lines and contributes to the growing body of literature on MNC activities in emerging economies by highlighting that product diversification impacts entry mode diversity and resource sharing across units.

City branding has gained popularity as governance strategy. However, the academic underpinning is still poor, and city branding needs a more critical conceptualization, as well as more complex management systems. This paper challenges the use of a “one size fits all” city brand, which is still common practice in many places. The paper proposes that city branding involves much more complexity than is commonly thought and outlines a strategy that enables urban policy-makers, marketing researchers and (place) marketers alike to better deal with city branding.

The authors integrate insights from literature on place branding, brand architecture and customer-focused marketing.

The article argues that place brands (in general and communicated place brands in particular) are by definition very complex, due to their different target groups, diverse place offerings and various associations place customers could have. Thus, an advanced brand management including target group-specific sub-brands is needed.

The model will be helpful for place brand managers dealing with a diverse target audience, and is likely to improve the target group-specific communication.

The paper provides an insight into the complexity of city brands and acknowledges that the perception of city brands can differ considerably among different target groups. Additionally, it offers a more comprehensive definition of place brands. This will be helpful for city brand managers and researchers alike in dealing with city brand complexity.

The purpose of this research work is to examine the financial effect of supply chain disruptions (SCDs) caused by coronavirus disease 2019 (COVID-19) and how the magnitude of such effects depends on event time and space that may moderate the signaling environment for shareholder behaviors during the pandemic.

This study analyses a sample of 206 SCD events attributed to COVID-19 made by 145 publicly traded firms headquartered in 21 countries for a period between 2020 and 2021. Change in shareholder value is estimated by employing a multi-country event study, followed by estimating the differential effect of SCDs due to the pandemic by event time and space.

On average, SCDs due to pandemic decrease shareholder value by −2.16%, which is similar to that of pre-pandemic SCDs (88 events for 2018–2019). This negative market reaction remains unchanged regardless of whether stringency measures of the firm's country become more severe. Supply-side disruptions like shutdowns result in a more negative stock market reaction than demand-side disruptions like price hikes. To shareholder value, firm's upstream or downstream position does not matter, but supply chain complexity serves as a positive signal.

This study provides the first empirical evidence on the financial impact of SCDs induced by COVID-19. Combining with signaling theory and event system theory, this study provides a new boundary condition that explains the impact mechanism of SCDs caused by the pandemic.

Green innovation can promote both environmental sustainability and economic growth. However, its development and implementation can be complex due to the need to align innovation activities within and across companies. In this study, the authors examined how this complexity can be managed by analyzing how individual companies combine different innovation activities to develop green innovation, and how companies along the value chain align to implement these innovations.

The dataset comprises both interviews and a survey of senior executives from the Swedish wood construction industry. These data were first analyzed by using fuzzy set qualitative comparative analysis (fsQCA) to identify innovation activity configurations at the level of the individual company. The interviews were then analyzed to identify alignment mechanisms enabling the implementation of green innovation along the value chain.

At the company level, the authors found three innovation activity configurations with varying levels of complexity: (1) systemic innovation by proactive companies, (2) process innovation by reactive companies and (3) inaction by technology-independent companies. On the value chain level, the authors found three alignment mechanisms that facilitate the implementation of green innovation along the value chain. These mechanisms promote cooperation by increasing efficiency, opening up new market opportunities and increasing the level of servitization.

This paper analyzes the complexity of green innovation and provides novel insights into how complexity is managed at the level of both the individual company and the value chain.

This paper aims to conceptualize supply market orientation (SMO) for the purchasing and supply chain management function and discusses how SMO capabilities are developed and how their application differs within and across firms. This research can thus be used as a blueprint for the development of a SMO capability that accommodates a firm’s unique contextual antecedents’ profile.

The qualitative research design comprises five in-depth case studies with 43 semi-structured interviews with large manufacturing and service firms.

SMO is defined as the capability to exploit market intelligence to assess, integrate and reconfigure the heterogeneously dispersed resources in purchasing and supply chain management in a way that best reflects the peculiarities of a firm’s supply environment. The empirical analysis shows that although SMO capabilities are configured similarly, their application varies across and within firms depending on the characteristics of a firm’s purchasing categories and tasks. Hence, reactive versus proactive SMO application is contingent upon firm-level and purchasing category–level characteristics.

The study uses the dynamic capabilities view as a theoretical background and provides empirical evidence and theoretical reasoning to elaborate and endorse SMO as a dynamic capability that firms need to have to compete in a complex and dynamic environment. The study provides guidance for supply chain managers on how to successfully develop and deploy a SMO capability.

This study investigates the relationship between the Chief Executive Officer's (CEO) overconfidence and financial reporting complexity in Iran, a context characterized by weak corporate governance and heightened managerial discretion.

The sample consists of 1,445 firm-year observations from 2010 to 2021. CEO overconfidence (CEOOC) is evaluated using an investment-based index, specifically capital expenditures. Financial reporting complexity (Complexity) is measured through textual features, particularly three readability measures (Fog, SMOG and ARI) extracted from annual financial statements. The ordinary least squares (OLS) regression is employed to test the research hypothesis.

Results suggest that CEOOC is positively related to Complexity, leading to reduced readability. Additionally, robustness analyses demonstrate that the relationship between CEOOC and Complexity is more distinct and significant for firms with lower profitability than those with higher profitability. This implies that overconfident CEOs in underperforming firms tend to increase complexity. Also, firms with better financial performance present a more positive tone in their annual financial statements, reflecting their superior performance. The findings remain robust to alternative measures of CEOOC and Complexity and are consistent after accounting for endogeneity issues using firm fixed-effects, propensity score matching (PSM), entropy balancing approach and instrumental variables method.

This study adds to the literature by delving into the effect of CEOs' overconfidence on financial reporting complexity, a facet not thoroughly investigated in prior studies. The paper pioneers the use of textual analysis techniques on Persian texts, marking a unique approach in financial reporting and a first for the Persian language. However, due to the inherent challenges of text mining and feature extraction, the results should be approached with caution.

The insights from this study can guide investors in understanding the potential repercussions of CEOOC on financial reporting complexity. This will assist them in making informed investment decisions and monitoring the financial reporting practices of their invested companies. Policymakers and regulators can also reference this research when formulating policies to enhance financial reporting quality and ensure capital market transparency. The innovative application of textual analysis in this study might spur further research in other languages and contexts.

This research stands as the inaugural study to explore the relationship between CEOs' overconfidence and financial reporting complexity in both developed and developing capital markets. It thereby broadens the extant literature to include diverse capital market environments.

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.