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This investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.

In this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

The provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.

In this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.

In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

This study analyses the effects of firm efficiency on firm performance and how controlling shareholders moderate the link between the two variables.

This study employs data envelopment analysis to estimate firm efficiency and the panel regression method to assess the hypothesised relationships among 1,295 firm-year observations of publicly listed firms in Malaysia from 2015 to 2019.

The results indicate that firm efficiency (technical efficiency, pure technical efficiency and scale efficiency) has mixed relationships with firm performance (return on assets, market-to-book ratio and operating cash flows), all of which are being moderated by controlling shareholdings.

This study highlights the importance of assessing firm efficiency as the key success factor for improving firm performance. Industrial managers should manage efficiently their resources or operating costs in achieving their corporate financial goals. Moreover, this study notes the presence of controlling shareholders, who can be either self-interested or company goal aligned.

This study suggests becoming efficient in transforming inputs into outputs is a prerequisite before investigating accrual-based and cash-based firm performance measures, and the presence of controlling shareholders matters in these regards.

This study examines the effect of value-added (VA) intellectual capital on business performance from the perspective of productive efficiency, which is derived from its main contributors, namely, profitability and marketability efficiencies in two stages.

First, this study applies a dynamic network slacks-based measure in a data envelopment analysis (DEA) approach to estimate productive efficiency and its components of 766 Taiwan listed electronics companies over the period of 2010–2018. Second, this study performs regression analyses of the association between intellectual capital (IC), which is proxied by VA intellectual coefficient (VAIC^TM) and estimated DEA efficiency scores through various regression techniques.

Empirical evidence shows a significantly positive association between VAIC^TM and productive efficiency. This study finds the same result from the IC components after splitting VAIC^TM into (1) IC efficiency, which comprises human capital efficiency (HCE) and structural capital efficiency and (2) capital employed efficiency. Further examination reveals that HCE is the sole main contributor of the productive efficiency, and profitability and marketability efficiencies of a company.

The findings of this study highlight the need to discuss the values of intellectual coefficient (IC) from the perspective of productive efficiency for better comprehensiveness.

Although previous studies have shown that IC is a contributor of business performance, this study further zooms in VAIC and examines its effect on the efficiency of a company in transforming its inputs into outputs.

This study aims to identify the inputs from zakat administrators and experts needed for more efficient and effective zakat revenue generation.

Face-to-face interviews with zakat executives, administrators and experts are conducted to collect data.

The findings show three components of input required in the zakat transformation: environment, resources and history. The environmental component comprises five sub-components: companies, banks, zakat recipients, individual zakat payers and the legislative, while the resource sub-components comprise tangible and intangible resources. For history, two components, namely, achievements and challenges, need to be taken into account by the zakat administration.

This study’s main implication is that the components proposed in this study can serve as the basis for developing new strategies for improving zakat collection and distribution management to achieve a more efficient and effective level.

This study will be helpful for policymakers, especially zakat authorities, on how to enhance their administration.

The model developed in this study will help the zakat administration to reform and enhance zakat compliance and zakat revenue generation.

This study aims to investigate the conflicting views in supply chain and strategic management literature regarding cooperative supply chain relationships (CSCR) and firm performance. Supply chain literature suggests a universally positive impact of CSCR on performance, irrespective of a firm’s strategy. In contrast, strategic management literature contends that the effectiveness of CSCR depends on their alignment with the firm’s competitive strategy. The research aims to clarify this disparity, offering insights into the strategic use of CSCR for enhancing firm performance.

This paper theorizes the integration of perspectives for the impact of CSCR on firm performance by examining the relationships considering the alignment of cost leadership and product differentiation strategies with supplier and customer relationships. Plant-level survey data is analyzed using regression techniques to test four hypotheses.

All four main relationships (cost leadership, product differentiation, supplier relationship and customer relationship) on firm performance are statistically significant. However, cost leadership firms are better aligned to their chosen strategy when they have strong relationships with suppliers, whereas similar relationships with customers create misalignment, negatively influencing firm performance. In contrast, product differentiators benefit by investing in relationships with customers rather than with suppliers.

A firm’s performance does not solely depend on its CSCR efforts but on aligning them with the firm’s overall strategy. Therefore, managers need to be cognizant of the firm’s competitive strategy when investing in CSCR. Failing to do so could negatively impact firm performance and, eventually, its ability to compete in the marketplace.

Scholars have advocated for the importance of examining competing perspectives of phenomena, both within and across various bodies of literature, as cross-disciplinary analysis often brings enhanced focus and depth, leading to improved understanding. This research is one of the initial efforts to empirically analyze the varying perspectives on CSCR in supply chain and strategic management literature. This cross-disciplinary approach can yield a more integrated perspective.

Work crew productivity and the application of limited resources are necessary elements in construction duration delay analysis. This study thus proposes a method to analyze construction delays and resource reallocation based on work crew productivity and resource constraints. The study also presents an economic feasibility analysis that maximizes economic effect by reducing construction duration, the cost of resource reallocation, delay liquidated damages (DLDs) and incentives for reducing contractual duration.

The proposed method involved three steps. First, work crew characteristics such as productivity, unit price and workload helped analyze delay information, including delay duration, reducible duration and daily reduced cost. Next, a goal programming method assessed resource reallocation based on the priority (as determined by decision-makers) of each constraint condition, such as the available number of workers, cost, goal workload and statutory working hours. Lastly, the level of reallocation was analyzed based on the results of the economic feasibility analysis and decision-makers’ delay attitudes.

A case study was performed to test the proposed method's applicability. Its involved sensitivity analysis indicated proposing to decision-makers a scenario based on the prioritization of economic feasibility. The proposed method's applicability proved high for decision-makers, as they can determine whether to reduce construction duration per the proposed data.

The proposed method's main contribution is the reallocation of resources to reduce construction duration based on work crew productivity and the prioritization of limited resources. The proposed method can analyze the differences in productivity between the plan and actual progress, as well as calculate the necessary number of workers. Decision-makers can then reduce the appropriate level of contractual duration based on their own delay attitude, constraint condition prioritization and results from daily economic feasibility analyses.

The purpose of this study is to evaluate the efficiency of the relative performances of Mother’s canteen across the regions of Tamil Nadu and find out the determinants of inefficiencies in the scheme.

An untargeted food security scheme called Amma (Mother's) canteen was started in Tamil Nadu, India, with an aim to provide the urban poor with hygienic and healthy food at an affordable price. Along with secondary data, interviews were conducted to understand the operational details of Mother's canteen. Data envelopment analysis (DEA) was used to find the relative efficiency of the scheme operated by nine corporations.

Based on the daily expenditure, number of meals served and revenue, seven of nine corporations were found to be inefficient. Further, sensitivity analyses found that among six procurement variables, procurement (quantity and price) of black gram and cooking oil were determinants of inefficiency.

As an untargeted scheme, the cost of delivering service-based evaluation was used for performance evaluation. Policymakers could use centralized procurement instead of open market procurement at the corporation level and standardized ingredients' usage (quantity) to further reduce the cost of the food security scheme.

The proposed DEA model may be used by policymakers to empirically evaluate the food security scheme's delivery effectiveness across various corporations in a region. Inefficient branches are identified here with empirical support for further performance improvement changes.

There are limited number of studies evaluating untargeted schemes. This paper presents the challenges of evaluating an untargeted scheme which allows self-selection of beneficiaries. The outcome of this study will help in identifying inefficient corporations, and further, improve the performance and cost of delivering untargeted food security scheme.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.