Sustainability and performance assessment of smart rural mobility pilots: A multi-case study

Purpose The purpose of this paper is to develop a framework and key performance indicators (KPIs) to assess the sustainability of the manufacturing organizations along the integrated supply chain. Design/methodology/approach A systematic literature review of existing peer-reviewed articles has been carried out to understand the strengths and weaknesses of current frameworks. A sustainability assessment framework has been proposed for the manufacturing sector. KPIs to assess sustainability performance of manufacturing organizations are identified. An empirical study is carried out for the cement industry to test the proposed framework and KPIs. Findings The existing frameworks on sustainability assessment lacks an integrated assessment consisting product life cycle, resources, critical factors (product, process and policy), KPIs and their interrelationship with sustainability dimensions. In total, 121 KPIs are identified for sustainability assessment of manufacturing organizations. The empirical study of the Indian cement industry identifies 52 KPIs (17 social, 15 economic and 20 environmental), which are classified into 13 factors using exploratory factor analysis. Research limitations/implications The proposed framework is tested for the cement sector. More studies are required to validate and refine the framework to make it generalized for the manufacturing sector. Originality/value This study has developed for the first time a close interrelation among life cycle engineering, resources, critical factors, KPIs and sustainability dimensions.

The full integration of sustainability considerations into maintenance practices requires a close monitoring of maintenance impact through appropriate key performance indicators (KPIs) that take into account various sustainability aspects. However, there is a lack of a comprehensive framework of KPIs covering all the sustainability dimensions, and the few attempts to address this need are specific to certain industries and lack validation by experts in the field. Therefore, the aim of this research is to develop and validate a comprehensive and multidimensional framework of sustainability performance indicators for the assessment of maintenance impacts on the triple-bottom-line. To that end, an exhaustive list of general indicators is collected based on both international organizations standard-sets and published literature. Subsequently, this list is projected on the maintenance area to establish the pertinent indicators. Then, a validation phase is performed with a highly qualified expert panel through semi-structured questionnaires and follow-up discussions. The validated list of sustainable maintenance KPIs includes 63 indicators amongst which 34 belong to the environmental pillar and are split between various categories such as resource use, residuals, environmental compliance, etc. The social pillar comprises of 15 indicators related to occupational health and safety, training and development and customer satisfaction dimensions. Finally, the economic pillar includes 14 indicators split between economic performance and investment categories. The findings of this research provide guidance to practitioners in the field and set the foundations for conducting promising future works. A rich portfolio of future research based on the obtained results is proposed.

Purpose– The purpose of this paper is to introduce a methodology to identify sustainable supply chain key performance indicators (KPI) that can then be used for sustainability performance evaluation for suppliers.Design/methodology/approach– Initially the complexity of sustainable supply chain performance measurement is discussed. Then, a two-stage method utilizing neighborhood rough set theory to identify KPI and data envelopment analysis (DEA) to benchmark and evaluate relative performance using the KPI is completed. Additional analysis is performed to determine the sensitivity of the KPI set formation and performance results.Findings– The results show that KPI can be determined using neighborhood rough set, and DEA performance results provide insight into relative performance of suppliers. The supply chain sustainability performance results from both the neighborhood rough set and DEA can be quite sensitive parameters selected and sustainability KPI sets that were determined.Research limitations/implications– The data utilized in this study are illustrative and simulated. Only one model for the neighborhood rough set and DEA was utilized. Additional investigations using a variation of rough set and DEA models can be completed.Practical implications– This tool set is valuable for managers to help identify sustainable supply chain KPI (from among hundreds of potential measures) and evaluate sustainability performance of various units within supply chains, including supply chain partners, departments, projects and programs.Social implications– Sustainability incorporates many business, economic and social implications. The methods introduced in this paper can help organizations and their supply chains become more strategically and operationally sustainable.Originality/value– Few tools and techniques exist in the sustainable supply chain literature to help develop KPIs and evaluate sustainability performance of suppliers and the supply chain. This paper is one of the first that integrates neighborhood rough set and DEA to address this important sustainable supply chain performance measurement issue.

Mobility is a popular topic in the fields of humanities and social sciences. China’s rapid urbanization has resulted in the acceleration of urban–rural mobility. Moreover, the implementation of the New Urbanization and Rural Revitalization Strategy has demonstrated the prospects of urban–rural integration and development. However, research on rural mobility is mainly focused in the fields of economics and sociology, with insufficient attention paid to spatial mobility. The main purpose of this study is to introduce a new theoretical explanation of the four dimensions of rural mobility based on a complete understanding of the current socio-economic background, namely, network mobility, green mobility, people-oriented mobility, and smart mobility. On this basis, a rural mobility evaluation index system is proposed by attempting to build a synthetic rural mobility index from the four aforementioned dimensions. Qingyang, a typical city in Western China located in the Loess Hilly Region, is taken as an example. Accordingly, the comprehensive rural and four-dimensional mobilities are analyzed and evaluated, and the effectiveness of the index system is verified. Results show that Qingyang’s rural mobility is at a low level, but differences in the types of rural residents, districts and counties, and dimensions of mobility are observed. At the end of this paper, the inclusion of mobility promotion in the policy system of rural revitalization is emphasized.

The study empirically investigates the relationship between corporate governance and the triple bottom line sustainability performance through the lens of agency theory and stakeholder theory. We claim, in fact, that no single theory fully accounts for all the hypothesised relationships. We measure sustainability performance through manual content analysis on sustainability reports of the US-based companies. The study extends the existing literature by investigating the impact of selected corporate governance mechanisms on each dimension of sustainability performance, as defined by the GRI framework. Our approach allows to identify which governance mechanisms foster triple bottom line performance, also revealing that some mechanisms fit only specific dimension(s) of sustainability. The fact-based findings provide support for a new beginning in the theorising process in which the theories must try not only to provide rationale for the impact of corporate governance on sustainability, but also to explain which dimension of sustainability might be more affected. The most important implication for practitioners is the support for sustainability practices, which may be gained through implementation of particular corporate governance mechanisms. The findings contribute also to the improvement of the ongoing standard setting process, in particular as it concerns the in-depth revision of the economic dimension of sustainability carried out under the new GRI framework.

The aim of this study is to develop a framework for investigating a comprehensive set of Key Performance Indicators (KPIs) for the assessment of railway Intelligent Transportation Systems (ITS). The framework is established through four main steps: (1) development of a comprehensive set of KPIs for railway ITS; (2) validation of developed KPIs and collection of judgments from experts through a Delphi questionnaire; (3) evaluation of KPIs weights for assessing railway ITS with the Group Analytical Hierarchy Process (GAHP); and (4) presentation of a SWOT analysis for the developed KPIs by the authors. The results of the framework are presented as a set of 25 indicators for evaluation of railway ITS and their impacts. The framework could be helpful for selecting KPIs of ITS in another mode of transportation. Monitoring of the contributions of ITS towards sustainable railway can be achieved by a developed set of indicators which are classified in accordance with sustainable dimensions.

Многокритериальная оценка устойчивого (sustainable) и умного (smart) развития городов необходима для реализации нового стратегического направления трансформации городов c целью снижения их воздействия на окружающую среду, увеличения занятости и стимулирования экономического развития и улучшения качества жизни. Анализ показателей устойчивого и умного городского развития в 143 городах мира, включая Лондон, Нью-Йорк, Гонконг, Сан-Франциско, Лос-Анжелес, Сан-Паулу, Рио-де-Жанейро, Буэнос-Айрес, Париж, Берлин, Стокгольм, Москву, Пекин, Сеул, Сингапур, Шанхай, Сидней и Токио, проведен методом многокритериального оценивания по 20 индикаторам. Были выявлены основные факторы, влияющие на выбросы CO2 в городах, включая доли угля и возобновляемых источников (ВИЭ) в энергетике, уровень развития общественного транспорта, особенности велосипедного и пешеходного движения, степень переработки отходов, а также налог на выбросы углерода. Результаты показывают, что среди глобальных городов Сан-Франциско лидирует при выборе экономических и экологических факторов как приоритетных, Стокгольм – при выборе в качестве приоритетных социальной направленности и разумности развития. Сеул показывает очень хорошие показатели по всему спектру индикаторов. В статье обсуждаются стратегии, средства и показатели, которые позволяют городам лидировать в направлении устойчивого и умного развития. Такой подход может быть полезен для лиц, принимающих решения, а также для инвесторов, и может помочь в идентификации связей между различными сторонами устойчивого и умного развития, а также выявлению потенциала устойчивого развития и инвестиционных возможностей в городах.

A new strategic direction for ‘greening’ our cities and making them smart to reduce the environmental impact of their performance, increase employment and economic viability and enhance the quality of life requires a thorough assessment of sustainability and smart urban performance. This chapter considers a database of over ninety global cities including London, New York, Hong Kong, San Francisco, Los Angeles, São Paolo, Rio de Janeiro, Buenos Aires, Paris, Berlin, Stockholm, Moscow, Beijing, Seoul, Singapore, Shanghai, Sydney and Tokyo, exploring linkages between different sustainability and smart city dimensions. To assess urban sustainability performance, the chapter applied a multi-criteria approach using a panel of twenty indicators to a set of fifty-seven global cities. The assessment comprised important aspects of energy transitions, focusing on the drivers of CO2 emissions in cities, including the share of coal in the energy mix, public transport and cycling patterns, waste recycling, the water-energy nexus as well as the role of smart and creative economy. The results have shown San Francisco leads under economic and environmental priorities, and Stockholm under social and smart city priorities. Seoul consistently performs very successfully across the whole spectrum of indicators. We devote considerable attention to strategies, policies and performance of the leading cities: San Francisco, Stockholm and Seoul. The assessment could be a valuable tool for policy makers and investors, and could help identify linkages between different sustainability dimensions as well as investment opportunities in cities with sustainability potential.

A new strategic direction for greening our cities and making them smart to reduce the environmental impact of their performance, increase employment and economic viability, and to enhance the quality of life requires a thorough assessment of sustainability and smart urban performance. This paper considers a database of over 90 global cities including London, New York, Hong Kong, San Francisco, Los Angeles, Sao Paolo, Rio de Janeiro, Buenos Aires, Paris, Berlin, Stockholm, Moscow, Beijing, Seoul, Singapore, Shanghai, Sydney and Tokyo exploring linkages between different sustainability and smart city dimensions. To assess urban sustainability performance, this study applied a multi‐criteria approach using a panel of 20 indicators to a set of 57 global cities. The assessment comprised important aspects of energy transitions, focusing on the drivers of CO2 emissions in cities, including the share of coal in the energy mix, public transport and cycling patterns, waste recycling, the water‐energy nexus, as well as the role of smart and creative economy. The results show that San Francisco leads in economic and environmental priorities, and Stockholm leads in social and smart city priorities. Seoul consistently performs very successfully across the whole spectrum of indicators. We devote considerable attention to the strategies, policies and performance of the leading cities, namely, San Francisco, Stockholm and Seoul. This assessment could be a valuable tool for policy‐makers and investors, and could help identify linkages between different sustainability dimensions, as well as investment opportunities in cities with sustainability potential.

This study examines how machine learning techniques can be used to predict Turkey's national sustainability performance in a comprehensive and data‐driven manner. Sustainable development is a multidimensional concept shaped by economic, social, environmental, and technological factors, making its assessment challenging through traditional analytical methods. Using official national and international data covering the period 2000–2022, this study develops predictive models based on key sustainability indicators. Several machine learning algorithms are applied and compared to evaluate their ability to capture complex relationships among sustainability dimensions. The results show that machine learning models can successfully forecast Turkey's sustainability performance with high accuracy, highlighting the importance of technological capability, economic structure, social development, and environmental conditions. The findings demonstrate the potential of machine learning as a decision‐support tool for sustainability monitoring and policy design. This study contributes to the literature by providing a replicable framework for national‐level sustainability assessment and offers practical insights for policymakers seeking evidence‐based strategies to support sustainable development goals (SDGs). From a policy perspective, the results provide concrete guidance for Turkey and similar developing countries by highlighting priority areas such as digital infrastructure, innovation capacity, female employment, and renewable energy policies to improve long‐term sustainability performance.

To address the challenges of sustainable manufacturing, precise, transparent and standardized sustainability assessment is essential. In this regard, normalization and weighting approaches are key tools to improve the precision, transparency and robustness of sustainability assessment efforts. However, mostly, the available literature on sustainability assessment discusses less about normalization and weighting. Moreover, previously, most of the related sustainability assessment and review studies were based on normalization and weighting for life cycle assessment (environmental dimension) only. Thus, this paper aims to present the recent status quo of normalization and weighting practices for sustainability assessment in manufacturing. Unlike previous review studies, this paper includes all three dimensions of sustainability (environment, economy and society). In order to achieve this objective, recent sustainability assessment studies (published in last 10 years) were reviewed and analyzed, from normalization and weighting viewpoints. The results showed that a majority of the reviewed studies which considered all three dimensions of sustainability were based on internal normalization. In contrast, the environmental assessment based studies were mostly grounded on external normalization. In addition, most of the reviewed studies considering all three dimensions of sustainability were concerned with normalization of input and/or output indicators, whereas environment based studies were mostly normalized for impact indicators. For weighting purposes, the analytic hierarchy process method was used most commonly, whereas the Delphi method and others were less frequently employed. Overall, more future work is required to increase awareness and usage of normalization and weighting methods for sustainability assessment in manufacturing.

A multi-criteria model of supply chain sustainability assessment and improvement for sugarcane agroindustry

PurposeThe purpose of this paper is to develop a sustainability readiness assessment model and a sustainability assessment model for manufacturing organizations.Design/methodology/approachThe proposed models have been developed using resource-based theory along the integrated supply chain. The models are based on resources sustainability (people, money, material, energy, infrastructure, water, and air), critical factors of sustainability (product, process and policies), sustainability dimensions (environment, economic, and social), and life cycle sustainability (integrated supply chain).FindingsThe paper presents an integrated assessment system which includes: product life cycle, resources, critical factors (product, process, and policy), key performance indicators, and their interrelationship with sustainability dimensions. The three critical factors and all the important resources required by a manufacturing organization along the integrated supply chain are identified. The readiness assessment model is user friendly and effective to guide the managers to identify the weak areas of sustainability.Research limitations/implicationsThe proposed model for readiness assessment is tested and in an automotive manufacturing organization but the sustainability assessment model is conceptual and it requires validation by implementing the same in an organization to understand its effectiveness.Practical implicationsThe readiness assessment model can help the top management to decide whether the organizational orientation is correct to improve sustainability. The easy to use models can be used by the decision/policy makers and independent bodies to assess, compare and benchmark the products, processes or organizations and thus affect public policies and attitudes.Originality/valueThis study has developed, for the first time, a sustainability readiness assessment model. The resource-based theory has been applied along the integrated supply chain.

Sustainability performance can be said to be an ability of an organization to remain productive over time and hold on to its potential for maintaining long-term profitability. Since the brewery sector is one of the most important and leading markets in the foodstuff industry of the Czech Republic, this study depicts the Czech breweries’ formal entry into sustainability reporting and performance. The purpose of this paper is to provide an efficiency level evaluation which would represent the level of corporate performance of Czech breweries. For this reason, Data Envelopment Analysis (DEA) is introduced. In order to apply it, we utilize a set of key performance indicators (KPIs) based on two international standard frameworks: the Global Reporting Initiative (GRI) and its GRI 4 guidelines, and the guideline KPIs for ESG 3.0, which was published by the DVFA Society. Four sustainability dimensions (economic, environmental, social and governance) are covered, making it thus possible to adequately evaluate sustainability performance in Czech breweries. The main output is not only the efficiency score of the company but also the input weights. These weights are used to determine the contribution of particular criteria to the breweries’ achieved score. According to the achieved efficiency results for Czech breweries, the percentage of women supervising the company does not affect the sustainability performance.

The increasing importance of sustainability has put pressure on organisations to assess their supply chain sustainability performance, which requires a holistic set of key performance indicators (KPIs) related to strategic, tactical and operational decision making of firms. This paper presents a comprehensive set of KPIs for sustainable supply chain management using a mixed method approach including analysing data from the literature survey, content analysis of sustainability reports of manufacturing firms and expert interviews. A 3-level hierarchical model is developed by classifying the identified KPIs into key sustainability dimensions as well as key supply chain decision-making areas including strategic, tactical and operational. A novel multi-attribute decision-making (MADM) based sustainability assessment framework is proposed. The proposed framework integrates value focussed thinking (VFT), intuitionistic fuzzy (IF) Analytic Hierarchy Process (AHP) and IF Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The novelty of the research lies in (1) using a rigorous mixed method approach for KPIs identification and industrial validation (2) the development of a novel integrated intuitionistic sustainability assessment framework for decision making and (3) the innovative application of the proposed framework and associated methodologies in the context not explored before. The practical data on the performance ratings of various KPIs were obtained from the experts and a novel intuitionistic fuzzy TOPSIS was applied to benchmark the organisations for their sustainability performance. Furthermore, the case study shows the applicability of the proposed framework to evaluate and identify the problem areas of the organisations and yield guidance on KPIs by recognising the most significant areas requiring improvement. This research contributes to the practical implication by providing an innovative sustainability assessment framework for supply chain managers to evaluate and manage sustainability performance by making informed decisions related to KPIs.