Management Decision最新文献

Purpose

The increasing relevance of environmental, social and governance (ESG) engagement has attracted interest in its drivers and effects on business outcomes under different organizational settings. By focusing on family firms (FFs), we deepen both the role of business ethics as a predictor of enhanced ESG engagement and the link with improved corporate financial performance (CFP). In this way, we aim to provide new insights into the impact of business ethics and ESG engagement on FFs competitiveness.

Design/methodology/approach

Based on a worldwide panel of 335 FFs covering the 2002–2020 time horizon, this study adopts a two-stage Heckman model (1979) to empirically address two research questions: (RQ1) Do business ethics predict greater ESG engagement in FFs? (RQ2) Does ESG engagement positively affect the corporate financial performance (CFP) of FFs?

Findings

The results of the current study are twofold. First, we demonstrate that an ethical approach to business drives greater ESG engagement. Second, we show that higher levels of ESG engagement lead to improved financial performance in FFs.

Originality/value

Our study contributes to filling the knowledge gaps regarding the drivers and effects of ESG engagement in FFs. On the one hand, we demonstrate the positive connection between dimensions that have their own identity, such as business ethics and ESG constructs. On the other hand, by shedding light on the impact of ESG engagement on improved CFP, we contribute to solving the trade-off between economic and noneconomic FF goals.

Purpose

Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

Design/methodology/approach

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

Findings

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Originality/value

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.

Purpose

This paper has a dual purpose: to produce a clear panorama of microfactors behind the implementation of environmental, social and governance (ESG) in emergent economies, and to identify long-term versus short-term implications of ESG and its impacts on sustainable transformation. In particular, the paper investigates the moderating role of ownership concentration on ESG performance and firm value relationship in Southeast Asia during 2010–2022 and COVID-19 period 2020–2022.

Design/methodology/approach

By adopting stakeholder and agency theory lenses, this study analyzes 591 nonfinancial listed companies in Southeast Asia from 2010 to 2022 with 2,673 firm-year observations. Data has been collected from Refinitiv and companies' annual reports. Ordinary least squares (OLS) and two-stage least squares (2SLS) estimators are main strategies.

Findings

During 2010–2022, the links between ESG performances and firm value are negative. Ownership concentration negatively moderates the nexus between governance pillar and firm value in both short and long run. In COVID-19, ownership concentration also plays an antagonistic moderating role in ESG combined score-firm value association. The results show a crucial role of blockholders in Southeast Asian firms and their strong support to ESG in conquering crisis period, suggesting that managers develop balancing mechanisms in making ESG-related decisions; policymakers and regulators improve effective control instruments with strong legal systems and enhanced law enforcement to protect minority shareholders.

Originality/value

This is the first study to test the connection between ESG performance, ownership concentration and firm value in Southeast Asia that has: (1) utilized different proxies of firm value and ownership concentration in robustness tests, (2) controlled heteroskedasticity defects, (3) eliminated companies in the Banking and Finance sector from the sample to avoid distorting the conclusions and (4) empirically verified the driven role of governance pillar in ESG performance and ownership concentration reversely moderated the impact of governance pillar on firm value.

Purpose

This study aims to examine the impact of learning organizational culture on organizational effectiveness. The study also explores the role of employee work engagement as the intervening mechanism in the learning organizational culture-organizational effectiveness association.

Design/methodology/approach

The data were collected from middle and top managers using the survey approach from the manufacturing and services sectors in India. Structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA) were used to analyze the data.

Findings

We found that organizational effectiveness is positively affected by learning organizational culture and that employee work engagement mediates this relationship. Our findings provide an essential building block in the research of learning organizational culture, work engagement and organizational effectiveness.

Originality/value

This study establishes linkages among the variables of interest by examining the impact of a learning organizational culture and work engagement on organizational effectiveness. It augments the existing literature on organizational effectiveness by elucidating the role of a learning organizational culture and work engagement as critical enablers of organizational effectiveness. Additionally, the study furnishes empirical evidence demonstrating the mediating role of work engagement in the relationship between a learning organizational culture and organizational effectiveness.

Purpose

Grounded in the Social Exchange theory, this study focuses on the perception of digital leadership and innovative work behaviors. It also examines the complex effects of leader-member exchange, learning orientation, and innovation capabilities.

Design/methodology/approach

We undertake a quantitative approach using a two-wave longitudinal field survey of 440 employees and managers from various backgrounds working in the automobile industry in France.

Findings

The findings based on Structural Equation Modeling reveal that the perception of digital leadership leads to innovative work behavior while leader-member exchange moderates between the perception of digital leadership and learning orientation. The findings also support the mediating roles of learning orientation and innovation capabilities.

Originality/value

The study contributes important policy suggestions, raises queries for additional investigation, and suggests theoretical and practical implications for leadership and organizational environmental factors to foster innovative work behaviors in organizations.

Purpose

This study draws on insights from the theory of conservation of resources to explore the impact of servant leadership (SL), creative adaptability (CA), and psychological well-being (PWB) on the service recovery performance (SRP) of employees. More specifically, the objective of this study is twofold: one to ascertain whether employees' service recovery performance would increase significantly after their exposure to SL, and two, to determine whether CA and PWB serially mediate the link between SL and SRP.

Design/methodology/approach

To analyze the data collected from a sample of 371 air service providers’ front-line employees (FLEs), partial least squares structural equation modeling (PLS-SEM) was performed.

Findings

The result indicated that SL was positively related to SRP. Likewise, the results of the serial mediation analysis showed that CA and PWB independently and serially mediated the SL-SRP relationship. This study makes significant contributions to the literature on SL and SRP.

Originality/value

This study adds to the growing body of research on how FLEs effectively deal with customers who are dissatisfied with their service failure experiences. Specifically, this research expands on previous results by proving the favorable effect of leadership style on FLE’s service recovery performance. In addition, the current study examines how effective service recovery is by assessing the employee’s resources based on COR theory. Finally, this research provides new insight into the influence of SL on SRP through the serial mediation of CA and FLE’s well-being.

Purpose

Theories are crucial for addressing research questions and advancing the boundaries of knowledge. However, in the field of strategic management, the existence of diverse schools of thought from various disciplines, including economics, politics, and sociology, poses significant challenges for researchers seeking to develop theories for argumentation and theorization. In this study, we have conceptualized a novel approach to selecting an appropriate theory for addressing specific research questions.

Design/methodology/approach

Thought experiment, disciplined imagination, and a conceptual examination of a diverse set of theories.

Findings

Because the central focus in the field of strategic management revolves around how firms achieve sustainable high performance, a research question should initially clarify the fundamental phenomenological issues it aims to address. Subsequently, the process of problematization should identify the ontological assumptions and premises that establish a connection between the research question and existing theories. Finally, the identification and abstraction of rhetorical concepts derived from these assumptions and premises lead to theory selection criteria, namely connectedness, reliability, parsimoniousness, and falsifiability.

Research limitations/implications

Although we believe that our model for theory selection is generalizable to a wide range of management disciplines, we have primarily focused on its application in the field of strategic management. Future work could validate and further explore the applicability and effectiveness of this model in selecting appropriate theories for conceptual development in other domains.

Originality/value

While many researchers have proposed methods for writing theoretical papers, few have provided suggestions specifically focused on theory selection. This paper stands out as one of the few that not only attempts to address this gap but successfully develops a comprehensive model for theory selection.

Purpose

Multi-criteria methods represent an adequate tool for solving complex decision problems that provide real support to the decision maker in the choice process. This paper analyzes a decision problem that recurs over time using one of the newer methods as the Parsimonious AHP.

Design/methodology/approach

In this paper we integrated the P-AHP with: (1) the weighted average which takes into account the objectivity of the data; (2) ordered weighted average (OWA) aggregation operators that address the subjective nature of the data; (3) the Choquet integral and (4) the Sugeno integral which also considers the uncertain nature of the final ranking as it is defined on a fuzzy measure.

Findings

The present paper proves that variations in the final ranking, due to the different mathematical properties of the selected aggregators, are fundamental to select the best alternative without neglecting any characteristic of the input data. In fact, it is discussed and underlined how and why the best alternative is one that never excels but has very good positions with respect to all aggregation operator rankings.

Originality/value

The aim and innovation presented in this work is the use of the Parsimonious AHP (P-AHP) method in a dynamic way with the use of different aggregation techniques.

Purpose

This paper aims to (1) unveil how artificial intelligence (AI) can be implemented in growth-hacking strategies; and (2) identify the challenges and enabling factors associated with AI’s implementation in these strategies.

Design/methodology/approach

The empirical study is based on two distinct groups of analysis units. Firstly, it involves 11 companies (identified as F1 to F11 in Table 1) that employ growth-hacking principles and use AI to support their decision-making and operations. Secondly, interviews were conducted with four businesses and entrepreneurs providing consultancy services in growth and digital strategies. This approach allowed us to gain a broader view of the phenomenon. Data analysis was performed using the Gioia methodology.

Findings

The study firstly uncovers the principal benefits and applications of AI in growth hacking, such as enhanced data analysis and user behaviour insights, sales augmentation, traffic and revenue forecasting, campaign development and optimization, and customer service enhancement through chatbots. Secondly, it reveals the challenges and catalysts in AI-driven growth hacking, highlighting the crucial roles of experimentation, creativity and data collection.

Originality/value

This research represents the inaugural scientific investigation into AI’s role in growth-hacking strategies. It uncovers both the challenges and facilitators of AI implementation in this domain. Practically, it offers detailed insights into the operationalization of AI across various phases and aspects of growth hacking, including product-market fit, user acquisition, virality and retention.

Purpose

We introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.

Design/methodology/approach

This study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.

Findings

Taking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.

Research limitations/implications

Limited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.

Practical implications

The tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.

Social implications

The proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.

Originality/value

The integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.