COVID-19 crisis and resilience of tourism SME’s: a focus on policy responses

the resilience of small and medium-sized tourism enterprises during crisis periods. Proper selection and implementation of these policies is one of the major challenges facing tourism policy makers. The aim of this article is to propose a systematic framework for selecting government supportive policies that contribute effectively to resilience improvements of tourism SMEs during the COVID-19 disaster. After reading the international reports of the COVID-19 disaster carefully and using similar research findings in past disasters as the preliminary stage of framework development, a comprehensive list of country-based recovery policy responses as well as the critical success factors (CSFs) of tourism SMEs in the crisis recovery phase was extracted and then finalized in an expert-oriented process. In the next stage, the Z-SWARA was applied to weigh the CSFs. Then, four Z-MADM methods were implemented to rank the alternatives, and finally, the results were compounded with BORDA technique. The results of implementing the proposed framework in Iran’s tourism industry show that Disaster management planning capability, as well as Marketing management are the most important CSFs. Also, financial support including direct lending and grants and subsidies to SMEs have been identified as the most effective governments’ supportive policies to recover tourism SMEs in the post-disaster phase. Generally, these results have valuable implications for different stakeholders such as policymakers, practitioners and researchers in the tourism industr

Developing a Conceptual Framework for the Scientific Social Networks using Metasynthesis Method

Scientific social networks play an important role in creating, organizing, storing, sharing, disseminating, and using information and knowledge among scientific communities and accelerate and facilitate the processes of information and knowledge management and communication among them. So the purpose of this research was to identify the dimensions and components of scientific social networks and to present its conceptual framework. This applied research has used a metasynthesis approach and library methods. A total of 50 sources out of 325 sources were selected for the meta-study and 170 codes, 25 concepts and 8 categories extracted. To analyze the data, seven step-by-step methods of Sandelowski and Barroso have been used. The findings showed that the components of scientific social networks, including: Management (science development, information management and knowledge management); Technology (information systems, scientific social websites, social networks); Culture (scientific behavior, scientific view, environmental and social factors); Communications (communication types and tools); Learning (education, content and cooperation); Personal characteristics (expert, skill, interest and motivation); Scientific performance (product, evaluation, assessment and scientific levels), and Legal issues (copyright and security) affect each other and scientific social networks. The proposed conceptual framework can be used for design, evaluation of success, assessment of status, prediction and pathology of scientific social networks in the scientific societies and centers

A multi-attribute framework for the selection of high-performance work systems: the hybrid DEMATEL-MABAC model

Research in strategic human resource management indicates that high performance work systems (HPWS) have a positive impact on the overall performance of an organization as a result of better human resource (HR) outcomes. Regarding the multi-dimensional and complex nature of these factors, common statistical models are not useful for examining the performance of HPWS. Using the capabilities of multi-attribute decision-making (MADM) methods to deal with various criteria that may be contradictory, this study proposes a MADM-based framework that provides the opportunity to prioritize HR practices. Based on this framework, high-performance HR practices and their related HR outcomes were identified after studying the theoretical literature and ascertaining the views of decision-makers and HR experts. Then, after looking at the interactions among HR outcomes, the weights of the criteria were calculated using the method of the decision making trial and evaluation laboratory (DEMATEL). Then, the alternatives were ranked using the multi-attributive border approximation area comparison (MABAC) method. Finally, the designed framework was implemented in an organization active in the banking industry. This framework can be used to improve employees’ performance and, consequently, the performance of the organization. Accordingly, taking into account the resource constraints organizations face, the priorities presented can be helpful in budgeting human-resource-management (HRM) improvement projects and making an appropriate resource allocation for this

Presenting the Conceptual model of the Social Knowledge Management using Meta Synthesis Method

Social knowledge management is an intersection between social knowledge management and social capital that plays an important role in extracting implicit social knowledge. The purpose of this research is to manage the social knowledge management of social network users. This research is an applied research that is done with meta-synthesis. To analyze the data, seven step-by-step methods of Sandloski and Baruso have been used. A total of 44 sources out of 258 sources were selected for the final meta-synthesis from which 224 codes, 25 concepts, and 8 categories were extracted and analyzed using Excel 2016 statistical software.The findings showed that the components of social knowledge management include intellectual capital (human, structural and communication); social capital (structural, cognitive and relational); knowledge management (knowledge dimensions, knowledge types, knowledge management processes, knowledge conversion, knowledge ecosystem and its obstacles); communications (personal and collective); learning (individual, collective and learning styles); leadership (management skills and management styles); culture (trust and interest and motivation); and technology (social media, semantic web and information and knowledge management systems). Also, findings showed that the knowledge and the social and intellectual capitals are components of the conceptual model of social knowledge management and this model is affected by communication, culture, technology and leadership factors and there are interactions between all of the above-mentioned elements. Generally, it can be said that the proposed conceptual model can help to evaluate the success factors of social knowledge management in organizations

A Hidden‎ Markov Model‎ ‎Based‎ ‎Extended Case-Based Reasoning Algorithm for Relief Materials Demand Forecasting

‎In emergency situations‎, ‎accurate demand forecasting for relief materials such as food‎, ‎water‎, ‎and medicine is crucial for effective disaster response‎. ‎This research is presented a novel algorithm to demand forecasting for relief materials using extended Case-Based Reasoning (CBR) with the best-worst method (BWM) and Hidden Markov Models (HMMs)‎. ‎The proposed algorithm involves training an HMM on historical data to obtain a set of state sequences representing the temporal fluctuations in demand for different relief materials‎. ‎When a new disaster occurs‎, ‎the algorithm first determines the current state sequence using the available data and searches the case library for past disasters with similar state sequences‎. ‎The effectiveness of the proposed algorithm is demonstrated through experiments on real-world disaster data of Iran‎. ‎Based on the results‎, ‎the forecasting error index for four relief materials is less than 10\%; therefore‎, ‎the proposed CBR-BWM-HMM is a strong and robust algorithm‎

Identifying and prioritizing cost reduction solutions in the supply chain by integrating value engineering and gray multi-criteria decision-making

Value engineering is an appropriate policy for creating and improving value, which reduces unnecessary costs and maintains core functionality. Despite the mentioned benefits, this approach has so far received little attention in the area of supply chain management. Although this approach is highly structured, limitations such as overemphasizing the cost criterion and failure to meet other criteria, utilizing team members’ votes to rank solutions, ignoring inherent uncertainty and ultimately disagreement between value engineering team members have reduced the effectiveness of this approach. The present study aims to provide a coherent framework for utilizing a value engineering approach to supply chain cost management and overcome the aforementioned limitations by utilizing gray multi-criteria decision-making. In this regard, in the first phase, the initial list of improvement solutions is determined, the criteria extracted from the literature are localized using value engineering team members’ opinion. These criteria are weighted using the gray stepwise weight assessment ratio analysis (SWARA-Gray) method. Then, the score of each solution is calculated by the value engineering team based on the list of criteria as a gray number. The scores are aggregated using the gray evaluation based on distance from average solution (EDAS-Gray) method, and the solutions are prioritized. Finally, the application of the proposed framework is investigated in a real case study in a power plant in Iran. The results of the research show that the final rankings of the solutions rarely changed for different methods; so the model used in this study has acceptable stability. First published online 24 September 202

Knowledge work difficulty factors: An empirical study based on different groups of knowledge workers

The determination of the difficulty factor in knowledge work can be important for improving the performance of knowledge workers. In this article a regression model for investigating the difficulty of knowledge based activities (KBAs) is proposed. Four factors are considered in the model: Uncertainty, Variability of information, Amount of information and Level of skill and expertise. An empirical study based on 119 jobs from three different groups of knowledge workers (i.e. managerial, professional and clerical) shows that there are significant differences between the difficulty of the KBAs in managerial, clerical and professional jobs, and that managerial KBAs are more difficult than the KBAs of the other two groups.  Furthermore, regression models indicate that Level of skill and expertise is the most influential factor in the difficulty of the KBAs in each of the three groups

Applying fuzzy integral for evaluating intensity of knowledge work in jobs

In this article, a framework is proposed to define and identify knowledge work intensity in jobs, quantitatively. For determining the Knowledge Work Intensity Score (KWIS) of a job, it is supposed that the job comprises some tasks and KWIS of the job is determined based on knowledge intensity of these tasks. Functional Job Analysis (FJA) method is applied to determine tasks of jobs and then Task’s Knowledge Intensity Score (TKIS) is computed by using Fuzzy integral method. Besides, importance weight and time weight of tasks are determined by utilizing appropriate methods. Finally, KWIS is calculated by a formula composed of tasks’ TKISs and the weights. For evaluating applicability of the framework, it is applied to calculate KWISs of two jobs (Deputy of Finance and service, Laboratory technician)

Prioritising IT Projects: A Multi-Method Approach

Effective project evaluation and selection has proven to have a direct and significant influence on organizations’ productivity and profitability. Therefore, researchers have been eagerly working on project selection mechanisms since mid-20th century, resulting in development of a plenitude of methods. However, most of prior studies are focused on proposing techniques for prioritising the projects based on a given set of selection criteria, with no or little emphasis on how such criteria themselves should be identified and prioritised in the first place, especially in situations where a large number of selection criteria is involved (which is today ubiquitous). This paper attempts to address this gap by combining fuzzy Quality Function Development with five Multi-Criteria Decision-Making (MCDM) methods. Five MCDM techniques are used and the results are aggregated to increase the robustness of our hybrid approach. The proposed approach is then applied in a numerical example from a real word IT organisation to illustrate the applicability and usefulness of the proposed methodology

Identify and prioritize Strategies to Reduce Plant Power Equipments Supply Chain Costs Through Value Engineering

Value engineering is one of the tools to create and improvement value while reduces unnecessary costs and keeps the original function, leads to increased efficiency. Today this technique used to reduce the cost in industries that are facing high costs such as the electricity industry. The evidence and expert’s opinion implying that many factors causing costs in the industry is related to the supply chain the low efficiency in the supply chain, resulting in increased costs. So to increase performance and reduce costs, the research was conducted aimed to identify and prioritize solutions reduce costs in the supply chain for cables and accessories combined cycle power plant Sirjan (Gol Gohar), who has a major role in the country's electricity supply. The final solutions for cost reduction after holding several meetings with experts of the project value engineering team were identified. Then these solutions were evaluated with criteria extracted of the research literature and opinions of experts of the project value engineering team were moderated and finalized. The final criteria and each of the sub-criteria were weighted by SWARA. Then final weight was calculated for each of the sub-criteria. In order to prioritize final solutions we used ARAS-G. After prioritizing solutions, solution the twelfth (reducing the time of order up to purchase and deliver through the reform procedures purchase), as the best solution was identified to reduce costs and thus increase performance supply chain targe