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The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.

In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.

Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.

Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.

Good management strives to align and corporate processes for more attention being paid to supply chain management. Firms realize that greater co-operation and improved coordination can help to manage the entire supply chain more efficiently. The imperfect quality item is one of the most important issues that affect the expected profit of green supply chain. The imprecise cost with screening process of poor quality items posed in supply chain is the subject of this study.

The present study explores production model for imperfect items having uncertain cost parameters with three-layer supply chain encompassing supplier, manufacturer and retailer. The model is considering the impact of business tactics such as order size, production rate, production cost and appropriate times in various sectors on collaborative marketing systems. Due to imprecise cost parameters, the pentagonal fuzzy numbers are set to fuzzify the total cost and defuzzifition by using graded mean integration.

This study offers an explicit condition in uncertain environment to manage the imperfect quality item to increase the potential profit of the supply chain. The influence of changes in parameter values on the optimal inventory policy under fuzziness is provided managerial insights.

This model makes a significant contribution to fuzzy inference. The results of the study provide a trading strategy for the industry to avoid losses. The prescribed study can be suitable for the industries like sculpture, jewelry, pottery, etc.

The study aims to investigate the Shari’ah governance quality effectiveness, at the bank and national levels, on the value relevance of Islamic banks’ (IBs’) earning per share and book value per share.

Quantitative analyses are conducted using a panel of 40 listed IBs from 12 countries during 2012–2019. Data were retrieved from the Refinitiv Eikon database and banks’ annual reports.

The findings suggest that Shari’ah supervisory boards’ attributes negatively influence the value relevance of accounting information while the internal procedures positively impact it. The results also provide evidence of a complementary effect between Shari’ah governance mechanisms at the bank and national levels on the value relevance of accounting information.

IBs’ boards and managers need to be more aware of the role of Shari’ah governance and its impact on value relevance. The observed complementarity between Shari’ah governance systems at the bank and national levels may incite regulators to include comprehensive Shari’ah governance regulations in their best practices. Strengthening collaboration between regulators and the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) is also required to create an enabling environment for investors to rely on the AAOIFI accounting standards in their investment decision-making process.

Existing studies tend to ignore the effectiveness of Shari’ah governance quality at the bank level on value relevance. There is a similar lack of empirical research on the effectiveness of the centralized Shari’ah governance scheme on accounting issues.

Despite the wide research and discussion on international performance, innovation and digital resilience dimensions of enterprises, the investigation and understanding of their interrelations seem to be limited. The purpose of this study is to identify the influential factors affecting the mentioned dimensions, determine the causal relationships among these identified factors and finally evaluate their importance in an aggregated framework from the viewpoint of small and medium-sized enterprises (SMEs).

A hybrid methodology is used to achieve the objectives. First, the main factors of international performance, innovation and digital resilience are extracted by an in-depth review of the literature. These factors are then screened by expert opinions to localize them in accordance with the conditions of an emerging economy. Finally, the relationship and the importance of the factors are determined using an uncertain multi-criteria decision-making (MCDM) approach.

The findings reveal that there is a correlation between digital resilience and innovation, and both factors have an impact on the international performance of SMEs. The cause-or-effect nature of the factors belonging to each dimension is also determined. Among the effect factors, business model innovation (BMI), agility, product and organizational innovation are known as the most important factors. International knowledge, personal drivers and digital transformation are also determined to be the most important cause factors.

This study extends the literature both in methodological and practical directions. Practically, the study aggregates the factors in the mentioned dimensions and provides insights into their cause-and-effect interrelations. Methodologically, the study proposes an uncertain MCDM approach that has been rarely used in previous studies in this field.

Sustainability is of growing significance in the contemporary business landscape as organizations strive to minimize their environmental impact and optimize supply chain (SC) operations. Gaining insights into the influence of Triple A SC practices on sustainable performance can offer valuable perspectives for practitioners and policymakers. This study aims to comprehensively review existing academic literature on Triple A supply chain management (SCM) and sustainability, examining its impact on sustainable performance while identifying key influencing factors.

This review follows the six steps and 14 decisions of conducting a systematic literature review to comprehensively review 57 papers published between 2004 and 2023.

Based on the content analysis of the selected papers, this study summarizes the antecedents, practices and outcomes of Triple A SCM, with a particular focus on its implications for sustainability. This paper builds a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of Triple A SCM.

This study establishes a connection between Triple A SCM and sustainable performance by examining its impact on economic, social and environmental aspects. This review identifies research gaps and acknowledges the lack of specificity in implementing Triple A SCM across diverse industries, regions and competitive markets with varying external environments. It emphasizes the necessity to customize approaches based on contextual factors and provides valuable recommendations for future research to advance the concept of Triple A SCM.

This research investigates whether focal firms employ strategic supply chain information disclosure, focusing on the concealment of supplier and customer identities, as part of their supply chain environmental risk management strategies (supplier sustainability risk and customer loss risk, respectively).

Using a panel dataset of Chinese listed firms from 2009 to 2019 and utilizing the suppliers’ environmental punishment of peer firms (peer events) as an exogenous shock and employing ordinary least squares (OLS) estimation, this study conducts a regression analysis to test how focal firms disclose the identities of their suppliers and customers.

Our results indicate that focal firms prefer to hide the identities of their suppliers and customers following the environmental punishment of peer firms’ suppliers. In addition, supplier concentration weakens the effect of withholding supplier identities, whereas customer concentration strengthens the effect of hiding customer identities. Mechanism analysis shows that firms hide supplier identities to avoid their reputation being affected and hide customer identities to prevent the deterioration of customers’ reputations and thus impact their market share.

Our study reveals that reputation spillover is another crucial factor in supply chain transparency. It is also pioneering in applying the anonymity theory to explain focal firms’ information disclosure strategy in supply chains.

This study aims to investigate the correlation between a CEO's business background and the readability of financial statement footnotes in Indonesia.

This study utilizes a sample period spanning from 2010 to 2018 and employs various statistical tests, including Propensity Score Matching (PSM), Coarsened Exact Matching (CEM) and the Heckman Model, to demonstrate that it can address issues of causality and endogeneity without introducing bias.

As a result, the findings of this study indicate a statistically significant negative relationship between CEOs with busy schedules and the readability of financial statement footnotes. This suggests that companies led by busy CEOs are more likely to have financial statement footnotes that are easier to read.

These findings hold significance for clarifying research related to the challenges of contextual analysis in financial statement footnotes, which are distributed by companies on a sentence-by-sentence basis.

The practical implications of the findings pertain to actionable steps that management can undertake and also offer regulators opportunities to monitor the potential for standard setting.

Based on the results presented, the authors are optimistic that the findings will pave the way for broader research on the impact of a busy CEO, encompassing not only financial aspects but also non-financial dimensions. The growing popularity of readability is driven by the proliferation of textual reports that pose challenges in analysis and raise numerous inquiries.

The purpose of this study is to explore the effect of backward supply chain information sharing (SCIS) on the performance of different parties along supply chains.

Using data collected from 617 Chinese manufacturers, this study examines the effect of information sharing from manufacturers to suppliers (ISMS) on supplier and manufacturer responsiveness in both two- and three-tier supply chains and the transferrable effect of information sharing from customers to manufacturers (ISCM) on supplier responsiveness. The authors use structural equation modeling and regression analysis to estimate the proposed relationships.

ISMS is positively related to supplier responsiveness in both two- and three-tier SCIS, whereas its effect on manufacturer responsiveness is conditional, indicating that upstream receiving parties benefit more from backward SCIS. ISCM is positively related to supplier responsiveness, demonstrating the transferable effect of backward SCIS.

When designing SCIS strategies, managers should take into account the unequal distribution of benefits from SCIS and the transferable effect of backward SCIS. Specifically, companies should always motivate their downstream partners to engage in SCIS, while they themselves need to be cautious with information sharing. They should also be aware that their information sharing behavior may benefit a third upstream party.

This study provides deep insights into the distribution of the benefits from SCIS among supply chain partners and suggests that the direction and the role supply chain partners play (as receiving or disclosing parties) in SCIS matter.

There is a compelling need for developing constructs in management science rather than adapting the constructs that have been developed in other domains. Having emerged in the 1950s, quality of work-life (QWL) measures have proved to be ineffective due to the lack of conceptual clarity and theoretical support. The article analyses the QWL measures highlights their coherence and verifies them for being used in specific contexts.

The study includes three stages to develop a QWL Measurement Scale. Fourteen questions were developed based on QWL concepts. They were validated using exploratory factor analysis (EFA) which split the dimensions into five factors. A survey was conducted on 375 medical residents. Finally, confirmatory factor analysis (CFA), convergence and validity were tested along the five dimensions.

Results extend the QWL concept and provide theoretical support for the same. Five dimensions were developed to measure QWL namely: pay and benefits, supervision, intra-group relations, working conditions and training.

The study may offer an overview of evaluation strategies to researchers and organizations that aim to improve employee QWL while they enhance its effectiveness through reliable instruments.

The scale developed in this study contributes to the body of QWL literature in the healthcare arena. It may be beneficial to carry out further research in this domain.