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1 – 10 of 347Melanie Durowse and Jane Fenton
This research was conducted as part of a PhD study. The purpose of this paper is to explore the factors taken into consideration when multi-agency practitioners were considering…
Abstract
Purpose
This research was conducted as part of a PhD study. The purpose of this paper is to explore the factors taken into consideration when multi-agency practitioners were considering financial harm in the context of adult protection and how this influenced their decision-making processes.
Design/methodology/approach
An adapted q sort methodology initially established the areas of financial harm considered to have additional factors, which led to complexity in adult protection decision making. These factors were further explored in individual interviews or focus groups.
Findings
The data identified that the decision-making process varied between thorough analysis, rationality and heuristics with evidence of cue recognition, factor weighting and causal thinking. This highlighted the relevance of Kahneman’s (2011) dual processing model in social work practice. Errors that occurred through an over reliance on System 1 thinking can be identified and rectified through the use of System 2 thinking and strengthen social work decision-making.
Originality/value
This paper considers the practice of multi-agency adult protection work in relation to financial harm and identifies the influences on decisions.
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Jan Svanberg, Tohid Ardeshiri, Isak Samsten, Peter Öhman, Presha E. Neidermeyer, Tarek Rana, Frank Maisano and Mats Danielson
The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted…
Abstract
Purpose
The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.
Design/methodology/approach
This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.
Findings
The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.
Practical implications
This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.
Social implications
The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.
Originality/value
To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.
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Ahmad Hariri, Pedro Domingues and Paulo Sampaio
This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.
Abstract
Purpose
This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.
Design/methodology/approach
A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.
Findings
The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.
Originality/value
There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.
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Alessandro Gaetano Naclerio and Pietro De Giovanni
This research investigates the effects that blockchain exerts on omnichannel solutions and logistics strategies with the aim of solving the last mile issues and improving…
Abstract
Purpose
This research investigates the effects that blockchain exerts on omnichannel solutions and logistics strategies with the aim of solving the last mile issues and improving performance.
Design/methodology/approach
Research hypotheses are developed according to the literature review and the related gaps. Then, the hypotheses are tested using structural equation modelling and adopting a partial least squares – path modelling technique on a dataset composed of 157 firms.
Findings
Blockchain technology alone is not an effective driver in solving last mile issues and improving performance. Rather, it exerts a positive contribution to both omnichannel and logistics. However, omnichannel is not effective in managing last mile problems and increasing performance without the support of other practices. Firms need to implement a strong logistics system to manage the last mile and get high performance, which can be then reinforced through blockchain and omnichannel solutions.
Originality/value
This research investigates the novel wave of research on blockchain and its impact on logistics management and omnichannel. It combines these ingredients to address the issues of last mile and improve the economic performance. The research provides an empirical verification of a new research stream that currently lacks empirical support.
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Joseph F. Hair, Pratyush N. Sharma, Marko Sarstedt, Christian M. Ringle and Benjamin D. Liengaard
The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis…
Abstract
Purpose
The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).
Design/methodology/approach
The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.
Findings
The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.
Research limitations/implications
In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.
Practical implications
The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.
Originality/value
To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.
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Zsolt Tibor Kosztyán, Tibor Csizmadia, Zoltán Kovács and István Mihálcz
The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk…
Abstract
Purpose
The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.
Design/methodology/approach
A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.
Findings
The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.
Originality/value
Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.
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This paper aims to analyze the benefits of the blockchain to the circular economy (CE), which is composed of both closed-loop supply chain (CLSC) systems and reverse omnichannel…
Abstract
Purpose
This paper aims to analyze the benefits of the blockchain to the circular economy (CE), which is composed of both closed-loop supply chain (CLSC) systems and reverse omnichannel solutions. By ensuring transparency, traceability, visibility and security, the blockchain allows firms to acquire operational capabilities through a CLSC and service capabilities through a reverse omnichannel, which can boost business performance considerably. The related network of relationships can be reinforced by establishing incentives, which entail both smart contracts in the blockchain and active return approaches in CE.
Design/methodology/approach
After identifying the boundaries of the theoretical framework, several research hypotheses are developed according to the literature review and emerging gaps. These gaps link to the impact of the blockchain on CE systems (CLSC and reverse omnichannel), as well as the influence on business performance. The hypotheses are then tested using structural equation modeling and adopting a partial least squares-path modeling technique on a dataset composed of 157 firms. Finally, multigroup analysis is used to test the impact of incentives on the research hypotheses.
Findings
The blockchain facilitates a more efficient CE system, although reverse omnichannel solutions seldom bring any benefits to performance. The shift from a passive to an active return approach must be carefully evaluated. The CLSC network can benefit from an active return approach by developing appealing incentives for collectors and enhancing the positive effects of the blockchain. In contrast, consumer incentives can have detrimental effects on the blockchain. Various combinations of incentives can only bring a few business performance increases, while collector incentives are vital to reinforce the CE system's operational and service capabilities.
Originality/value
This paper takes a new approach toward the study of CE, which considers a dual circular system composed of a CLSC and a reverse omnichannel. The research explores whether the adoption of blockchain technology enables better return processes by improving the operations in CLSC and services in reverse omnichannel. Finally, this is the first empirical work to evaluate the benefits emerging from incentives, which can activate smart contracts in the blockchain and enable active return approaches in CE.
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Diqian Ren, Jun-Ki Choi and Kellie Schneider
Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the…
Abstract
Purpose
Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.
Design/methodology/approach
The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.
Findings
To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.
Originality/value
This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.
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