Socio-economic Planning Sciences最新文献_第6页

Integrating circular economy principles into a modified theory of Planned Behaviour: Exploring customer intentions and experiences with collaborative consumption on Airbnb

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-12-05 DOI: 10.1016/j.seps.2024.102136

Umair Tanveer , Shara Nica Agung Sahara , Marios Kremantzis , Shamaila Ishaq

The sharing economy, exemplified by platforms like Airbnb, has significantly disrupted traditional business models through peer-to-peer sharing of underutilized assets. This study investigates the influence of circular economy (CE) principles and customers' past experiences on their intention to participate in collaborative consumption (CC), focusing on Airbnb. Despite economic, social, and environmental benefits, such as resource efficiency and community connections, concerns about affordable housing and community disruption persist. This research integrates CE principles into the Theory of Planned Behaviour (TPB), examining attitudes, subjective norms, and perceived behavioural control as predictors of CC intention. Using a quantitative research design, data were collected from an online survey of 449 Airbnb users. The study found that economic benefits substantially affected customer attitudes towards CC, while perceived behavioural control and subjective norms significantly influenced CC intentions. Interestingly, past experience negatively moderated the relationship between attitude and CC intention, indicating that frequent users prioritize cost savings over positive product assessments. These findings highlight the importance of emphasizing economic advantages in marketing and suggest the need for educational initiatives to reshape frequent users' perceptions. This research provides practical insights for Airbnb and other CC providers to develop targeted strategies promoting customer adoption. It also offers policymakers guidance for supporting CC growth and sustainability, enhancing the TPB framework by incorporating CE principles and past experience to offer a comprehensive understanding of factors influencing CC intentions.

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引用次数: 0

Does regional economic development drive sustainable grain production growth in China? Evidence from spatiotemporal perspective on low-carbon total factor productivity

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-12-03 DOI: 10.1016/j.seps.2024.102129

Ruixue Wang , Xiangzheng Deng , Yunxiao Gao , Jiancheng Chen

Contrary to conventional expectations, the impact of economic development on food green efficiency exhibits pronounced regional heterogeneity. This study utilizes total factor productivity (TFP) as a key metric, establishing a model for carbon emissions from grain production and developing a framework for measuring grain low-carbon TFP growth. Employing the undesirable super-slacks-based measure (SBM) and the Malmquist-Luenberger (ML) index, we assess the low-carbon TFP growth across 31 Chinese provinces from 2000 to 2021. The Dagum–Gini coefficient and variance decomposition are applied to analyze disparities from both regional and structural perspectives. An econometric model further validates the influence of economic development on low-carbon TFP growth. Our findings reveal that China's technical efficiency (TE) and low carbon TE initially show a declining trend, with the gap between them narrowing over time. The eastern region consistently demonstrates high low-carbon TE, while the northeastern region lags. All regions exhibit positive low-carbon TFP growth, with efficiency change (EC) significantly contributing to this growth. Although economic development generally fosters low-carbon TFP growth, marked regional heterogeneity persists. Interestingly, certain traditionally economically developed regions, such as the eastern region, exert a significantly negative impact on low-carbon TFP growth. Balancing economic development with low-carbon TFP growth remains an ongoing challenge that necessitates effective management strategies.

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引用次数: 0

Assessing changes in wealth index using primary survey data

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-12-01 DOI: 10.1016/j.seps.2024.102115

Sandeep Kumar , S. Chakraverty , Narayan Sethi

In this study, we have introduced a new method to develop the Wealth Index (WI). In this regard, primary survey data, along with secondary data obtained from the National Family Health Survey-4 (NFHS-4) and NFHS-5 datasets, is used to construct the WI for the Koraput district in the Indian state of Odisha. Furthermore, we compared the WI obtained from the primary data with the WI obtained from the NFHS-4 and NFHS-5 data sets for Koraput and Odisha. Furthermore, to analyze wealth disparities at a finer scale, we computed and compared sub-indices in a similar manner to the WI. To develop the WI, we adopted a novel approach based on principal component analysis (PCA) with orthogonal rotation of factors whose eigenvalue is greater than 1 to utilize the maximum variance of data. The results derived from the WI and its sub-indices indicate that, when contrasted with Odisha as a whole, Koraput exhibits a lower level of wealth. The findings also reveal that, over time, there has been some improvement in wealth conditions, but they remain a cause for serious concern. Overall, the WI for the said district presents critical results, underscoring the urgent need for government or NGO intervention.

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引用次数: 0

Equity and sustainability in the health care market: Socio-economic analysis of governance and reforms 保健市场的公平和可持续性：对治理和改革的社会经济分析

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-12-01 DOI: 10.1016/j.seps.2024.102074

Lucia Leporatti, Ching-to Albert Ma

引用次数: 0

Enhancing SMEs sustainable innovation and performance through digital transformation: Insights from strategic technology, organizational dynamics, and environmental adaptation

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-11-28 DOI: 10.1016/j.seps.2024.102124

Shaofeng Wang , Hao Zhang

With the advent of the digital wave, understanding the impact of Digital Transformation on sustainable development in firms is increasingly important. Drawing from the Technology-Organization-Environment (TOE) framework and the Dynamic capability view, this study investigates the determinants of Digital Transformation and its impact on Sustainable Innovation Capability and Sustainable Organizational Performance. Data from 261 firms were collected via surveys and analyzed using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The results demonstrate that Technology, Organization, and Environment are critical factors driving Digital Transformation. Digital Transformation can enhance Sustainable Organizational Performance by improving a firm's Sustainable Innovation Capability. Environmental Dynamism positively moderates the effect of Digital Transformation on Sustainable Innovation Capability and Sustainable Organizational Performance. Importance-performance map analysis (IPMA) confirms Digital Transformation as the most significant predictor of Sustainable Organizational Performance. fsQCA identifies three configurations leading to highly Sustainable Organizational Performance. These findings provide new theoretical evidence for understanding the relationships among Digital Transformation, Sustainable Innovation Capability, and Sustainable Organizational Performance and the moderating role of Environmental Dynamism in these relationships. This study offers a new perspective on the relationship between Digital Transformation and sustainable development and supports applying TOE framework, and Dynamic capability view. The results are significant for understanding the drivers of Digital Transformation and its impact on sustainable development in firms.

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引用次数: 0

Measuring efficiency in tourism: A problem of shared factors and multiple attributes in DEA

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-11-28 DOI: 10.1016/j.seps.2024.102117

Sonia Valeria Avilés-Sacoto , Estefanía Caridad Avilés-Sacoto , Wade D. Cook , David Güemes-Castorena

The current research makes three main contributions to the DEA (Data Envelopment Analysis) literature. First, when using DEA to derive an efficiency score for a given DMU, it is normally assumed that each and every DMU has its own unique set of inputs and outputs, there are situations whereby a DMU can have a factor that is shared with other DMUs. This means that one must view efficiency from the perspective of groups of DMUs rather than from the perspective of the individual DMU. Second, two stage problems can, in the presence of shared factors, result in different groupings of DMUs in one stage than in another. Third, in certain circumstances efficiency can be viewed from the perspective of multiple attributes (e.g. different types of tourism). Herein, we develop a model to cater for these features and illustrate the model using a data set on tourism in Mexico.

引用次数: 0

A sustainable vaccine supply-production-distribution network with heterologous and homologous vaccination strategies: Bi-objective optimization

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-11-26 DOI: 10.1016/j.seps.2024.102113

Ali Jahed , Seyyed Mohammad Hadji Molana , Reza Tavakkoli-Moghaddam

Heterologous and homologous Coronavirus Disease 2019 (COVID-19) vaccination against Severe Acute Respiratory Syndrome (SARS)-CoV-2 are robust and proactively adaptable strategies. However, there is still a lack of appropriate mathematical models for integrating vaccination strategies into the vaccine supply chain network. This study develops a supply-production-distribution-inventory-allocation problem in the Sustainable Vaccine Supply-Production-Distribution Network (SVSPDN) to fill this gap for the first time. The outstanding novelties of this research are prioritizing vaccines and sequencing injection doses to increase vaccination effectiveness. In addition, the remarkable new contribution of the proposed mathematical model is the design of new bi-objective, multi-dose, multi-level, and multi-period to ensure the sustainability performance of the entire network. This aim is achievable by minimizing the cost of supplying, producing, and distributing vaccines and fulfilling social goals by maximizing vaccination effectiveness. Also, a scenario-based robust stochastic optimization approach is presented to handle uncertainties. Since the SVSPDN design is an NP-hard problem, to solve the proposed mathematical model, three Pareto-based evolutionary algorithms, including Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Multi-Objective Gray Wolf Optimizer (MOGWO), are applied. The Taguchi design method is applied to tuning the parameters due to the sensitivity of meta-heuristic algorithms to input parameters. Then, a comparison is performed using four assessment metrics, including the Number of Pareto Solutions (NPS), Diversification Matrix (DM), Mean Ideal Distance (MID), Spread of Non-Dominance Solutions (SNS), and Computation Time (CT). The results reveal that the NSGA-II and MOGWO algorithms have performances that are very close to each other. However, MOGWO performs better in tackling the problem and is superior to the NSGA-II and MOPSO regarding assessment metrics and computation time. A case study of Iran is investigated to indicate the efficiency and applicability of the proposed model. Finally, sensitivity analyses, managerial insights, and practical implications are discussed.

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引用次数: 0

University student's opinion survey: A synthesis and a deeper insight 大学生意见调查：综合与深入洞察

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-11-25 DOI: 10.1016/j.seps.2024.102114

Silvia Terzi , Francesca Petrarca

This study evaluates the University Student's Opinion Survey (OPIS), which measures student satisfaction with university courses using a four-level Likert scale. We propose applying Alkire-Foster's dual cut-off method (Alkire and Foster, 2007; Alkire and Foster, 2011) [2,4] to compute a multidimensional performance indicator and a local concordance curve to detect the association between different dimensions of the performance indicator. In our analysis, we set benchmarks for each survey item to classify classes as effective or critical based on their performance across multiple dimensions. Additionally, we introduce local concordance coefficients to provide deeper insights into student evaluations across different performance areas. In particular, we assess whether there is a concentration of organizational and teaching deficiencies (strengths) among the critical (effective) classes or whether the lacking (appreciated) skills are equally distributed among the different dimensions investigated by the survey. This comprehensive approach, combining the Alkire-Foster method and local concordance analysis, underscores the importance of multidimensional perspectives in assessing teaching quality, providing valuable insights for enhancing educational experiences in higher education.

本研究评估了大学生意见调查（OPIS），该调查使用四级李克特量表衡量学生对大学课程的满意度。我们建议应用Alkire-Foster的双截止法(Alkire and Foster, 2007；Alkire and Foster, 2011)[2,4]计算多维绩效指标和局部一致性曲线，以检测绩效指标不同维度之间的关联。在我们的分析中，我们为每个调查项目设置基准，根据它们在多个维度上的表现将类分类为有效的或关键的。此外，我们引入了本地一致性系数，以便更深入地了解不同表现领域的学生评估。特别是，我们评估在关键（有效）班级中是否存在集中的组织和教学缺陷（优势），或者缺乏（赞赏）技能是否平均分布在调查所调查的不同维度中。这种综合方法结合了阿尔凯尔-福斯特方法和地方一致性分析，强调了多维视角在评估教学质量中的重要性，为提高高等教育的教育体验提供了有价值的见解。

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引用次数: 0

Modelling global fossil CO2 emissions with a lognormal distribution 用对数正态分布模拟全球化石二氧化碳排放量

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-11-22 DOI: 10.1016/j.seps.2024.102104

F. Prieto , C.B. García-García , R. Salmerón-Gómez

Carbon dioxide emissions have emerged as a critical issue with a profound impact on the environment and the global economy. The steady increase in atmospheric CO

_{2}

levels has become a major contributor to climate change and its associated catastrophic effects. A global effort is needed to tackle this pressing challenge, requiring a deep understanding of emissions patterns and trends. This paper focuses on identifying the underlying distribution of CO

_{2}

emissions analysing the hypothesis that the fossil CO

_{2}

emissions data, at the country level, can be described by a 2-parameter statistical model for the whole range of the distribution (all world countries). We consider that modelling with a simple distribution can be particularly useful in understanding CO

_{2}

emissions and we are looking to make our findings more accessible to policymakers. We utilize data from four databases and analyse six candidate distributions (exponential, Fisk, gamma, lognormal, Lomax, Weibull). Our findings highlight the adequacy of the lognormal distribution in characterizing emissions across all countries and years studied. A comprehensive analysis of Gibrat’s Law from 1970 to 2021 is also presented, employing a rolling window approach for the short, medium, and long term. Our findings reveal that Gibrat’s Law appears to be a short-term phenomenon for original CO

_{2}

emissions, but not for per capita emissions, aligning with conclusions from previous research. Finally, we employ the lognormal model to predict emission parameters for the coming years and propose two policies for reducing total fossil CO

_{2}

emissions.

二氧化碳排放已成为对环境和全球经济产生深远影响的关键问题。大气中二氧化碳含量的持续增加已成为气候变化及其相关灾难性影响的主要因素。要应对这一紧迫挑战，需要全球共同努力，这就要求深入了解排放模式和趋势。本文的重点是确定二氧化碳排放的基本分布，分析化石二氧化碳排放数据在国家层面上可以用一个针对整个分布范围（世界所有国家）的 2 参数统计模型来描述的假设。我们认为，用简单分布建模对理解二氧化碳排放特别有用，我们希望能让决策者更容易理解我们的研究结果。我们利用四个数据库的数据，分析了六种候选分布（指数分布、菲斯克分布、伽马分布、对数正态分布、洛马克斯分布、威布尔分布）。我们的研究结果凸显了对数正态分布在描述所研究的所有国家和年份的排放量特征方面的充分性。我们还采用短期、中期和长期的滚动窗口方法，对 1970 年至 2021 年的吉布拉特定律进行了全面分析。我们的研究结果表明，吉布拉特定律似乎是二氧化碳原始排放量的短期现象，但不是人均排放量的短期现象，这与之前的研究结论一致。最后，我们利用对数正态模型预测了未来几年的排放参数，并提出了减少化石二氧化碳排放总量的两项政策。

{"title":"Modelling global fossil CO2 emissions with a lognormal distribution","authors":"F. Prieto , C.B. García-García , R. Salmerón-Gómez","doi":"10.1016/j.seps.2024.102104","DOIUrl":"10.1016/j.seps.2024.102104","url":null,"abstract":"<div><div>Carbon dioxide emissions have emerged as a critical issue with a profound impact on the environment and the global economy. The steady increase in atmospheric CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> levels has become a major contributor to climate change and its associated catastrophic effects. A global effort is needed to tackle this pressing challenge, requiring a deep understanding of emissions patterns and trends. This paper focuses on identifying the underlying distribution of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions analysing the hypothesis that the fossil CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions data, at the country level, can be described by a 2-parameter statistical model for the whole range of the distribution (all world countries). We consider that modelling with a simple distribution can be particularly useful in understanding CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions and we are looking to make our findings more accessible to policymakers. We utilize data from four databases and analyse six candidate distributions (exponential, Fisk, gamma, lognormal, Lomax, Weibull). Our findings highlight the adequacy of the lognormal distribution in characterizing emissions across all countries and years studied. A comprehensive analysis of Gibrat’s Law from 1970 to 2021 is also presented, employing a rolling window approach for the short, medium, and long term. Our findings reveal that Gibrat’s Law appears to be a short-term phenomenon for original CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions, but not for per capita emissions, aligning with conclusions from previous research. Finally, we employ the lognormal model to predict emission parameters for the coming years and propose two policies for reducing total fossil CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"97 ","pages":"Article 102104"},"PeriodicalIF":6.2,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Variable RTS in hierarchical network DEA: Enhancing efficiency in higher education systems 分层网络 DEA 中的可变 RTS：提高高等教育系统的效率

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences

Pub Date : 2024-11-20 DOI: 10.1016/j.seps.2024.102112

Siwei Xiao , Marios Kremantzis , Leonidas Sotirios Kyrgiakos , Aniekan Essien , George Vlontzos

This study presents a novel approach to Network Data Envelopment Analysis (DEA) by introducing “Returns to Scale (RTS) separation” within a hierarchical network DEA framework. Traditional DEA models, which often assume constant RTS, face limitations when analysing complex multi-functional structures. The proposed method, Variable RTS in Hierarchical Network DEA (VRS-HNDEA), addresses these limitations by integrating variable RTS, enabling a detailed efficiency analysis across hierarchical systems with heterogeneous sub-units. By utilising free variables, this model establishes distinct efficiency planes for simultaneous benchmarking of diverse subsystems, yielding a global efficiency frontier through the Minkowski addition of sub-system sets and analysed using an input-oriented enveloped form. Applied specifically to the higher education sector, the VRS-HNDEA model provides insights into the operational efficiency of various academic functions, including teaching, research, and administration. Key findings from this application demonstrate the model's ability to capture efficiency variations across hierarchical levels, supporting nuanced decisions on resource allocation and scale optimization. This framework, with its capability to recognise scale diversity across sub-systems, offers a significant tool for enhancing efficiency assessment in multi-layered public sector contexts, such as higher education, where comprehensive resource management is crucial.

本研究提出了一种新颖的网络数据包络分析（DEA）方法，即在分层网络 DEA 框架内引入 "规模回报（RTS）分离"。传统的 DEA 模型通常假定 RTS 恒定不变，在分析复杂的多功能结构时面临局限性。所提出的方法，即分层网络 DEA 中的可变 RTS（VRS-HNDEA），通过整合可变 RTS 来解决这些局限性，从而能够对具有异构子单位的分层系统进行详细的效率分析。通过利用自由变量，该模型建立了不同的效率平面，可同时对不同的子系统进行基准测试，通过子系统集的闵科夫斯基加法得出全球效率前沿，并采用以投入为导向的包络形式进行分析。将 VRS-HNDEA 模型具体应用于高等教育领域，可以深入了解教学、研究和行政等各种学术职能的运行效率。这一应用的主要研究结果表明，该模型能够捕捉各层级的效率变化，为资源分配和规模优化方面的细微决策提供支持。该框架能够识别各子系统之间的规模多样性，为加强多层次公共部门（如高等教育）的效率评估提供了重要工具，因为在这种情况下，全面的资源管理至关重要。

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引用次数: 0