GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul,Turkey

Fire stations play a central role in protection and response activities as part of emergency management services in cases of fire incidences. With the rising urban populations and city expansions, the demand for more fire services resultantly increases. It then becomes critical to effectively plan the location of emergency facilities to adequately service the population and ensure the protection of lives and infrastructure. This study, therefore proposes the use of the fuzzy extension of the Multi-Criteria Decision-Making (MCDM) method of Analytical Hierarchical Process (AHP), hence called fuzzy AHP, integrated with Geographic Information Systems (GIS) approach to optimally site new fire stations for the case of Istanbul region. This proposed fuzzy approach simulates the subjective expert judgements for the preferences of the six criteria assessed for fire station suitability mapping and thereby accounted for the uncertainty of crisp comparison values via triangular fuzzy numbers (TFNs). The criteria weights evaluated from this procedure were used in a weighted overlay analysis of the reclassified criteria map layers in ArcGIS to generate a fire station suitability map. These resultant fuzzy AHP criteria weights were validated using another MCDM technique, called Best-Worst Method (BWM) and found to be comparable and consistent. The criteria that had the strongest influence on the selection of sites for fire stations were identified to be: the density of hazardous material facilities (DHM), a high population density (HPD) and proximity to main roads (PMR) with associated weights of 33.3%, 24.4% and 15.2%, respectively. Based on a thorough assessment within the areas represented by class values ranging from 3 to 5 on the suitability map, a total of 34 new fire station sites were selected complementing the existing 121 fire stations. Further, a prioritization analysis from low, medium to high, was performed to plan the phases for the construction of new fire stations in view of competing budgetary needs and resource constraints. The methodology to achieve this was proposed and modelled for enhancing the decision-making process in urban fire station site selection studies.     

A GIS-based multi-criteria decision analysis approach using AHP for rural settlement site selection and eco-village design in Erzincan,Turkey

In recent years, natural resource depletion, rapid population growth, and increasing urbanization have all reached new heights. All of these ecological problems that exceed the planet's absorbing capacity, have begun to imperil both human life and nature itself. Rural settlement plans aim to optimize the use of natural resources. Agricultural lands are used for non-agricultural purposes as a result of proper placement planning of rural settlements. The suitability of land for a specific purpose is determined via suitability analysis. Therefore, it is extremely important to use technological innovations in the selection of rural settlement areas in addition to considering the technical, economic, and social factors in determining the most suitable locations. With the advancement of computer technology, Geographical Information System (GIS) has become an important tool for more effective use of rural areas. In this study, the most suitable rural settlement area was determined by using GIS in Erzincan Province. Technical, social, cultural, and economic criteria were developed for the selection of the location. Alternative locations were analyzed using the GIS, Multi-Criteria Decision Analysis and the Analytical Hierarchy Process method based on the criteria and site data. The most suitable areas for rural settlements were chosen as the Merkez, Tercan, Kemaliye, and Kemah districts in Erzincan Province. Çağlayan town in the Merkez district has been determined as the most suitable region for an eco-village and a cost calculation and 3D eco-village design were carried out in Çağlayan.     

Value investing versus other investment strategies: A volatility spillover approach and portfolio hedging strategies for investors

Motivated by the incessant demand for portfolio diversification, this study examines the connectedness between value and diverse types of stocks (growth, momentum, ESG, high beta, classic S&P 500, volatility). The applied methodology encompasses the time-varying parameter vector autoregressive (TVP-VAR) extension of the Diebold and Yilmaz (2012) framework for the period from 03/31/2011 to 03/31/2021. Results show moderate volatility transmissions among the sampled assets, which tend to escalate during periods of turmoil, such as the European Sovereign Debt Crisis, the plunge in oil prices and the COVID-19 outbreak. Growth and ESG stocks play an indispensable part in the transmission mechanism. Moreover, we investigate the hedging ability of value stocks within a portfolio containing other stocks, by estimating hedge ratios and optimal weights with the usage of conditional variance estimates (DCC-GARCH). The empirical findings reveal that value stocks can adequately hedge against the risk deriving from the volatility of the remaining investment instruments, especially in the case of high beta and volatility stocks. Thus, this analysis provides portfolio managers and investors with valuable insights in order for them to hedge their stock portfolios effectively.     

Effects of standardization and innovation on mass customization: An empirical investigation

Mass customization (MC) refers to the capability to produce customized goods for a mass market. Innovation can enhance the flexibility and responsiveness of a company, and standardization enables the company to achieve economies of scale and scope, both of which are necessary for developing MC capability. A conceptual model is proposed to explore the relationships among innovation, standardization, MC capability, and delivery speed. Hypotheses are tested using survey data from 204 manufacturing companies in China. The results show that standardization positively influences innovation. Innovation and standardization positively affect MC capability and are complementary in developing MC capability. Innovation significantly enhances delivery speed. However, the direct effect of standardization on delivery speed is nonsignificant. In addition, innovation and standardization indirectly affect delivery speed through MC capability. This study contributes to the literature by providing empirical evidence on the individual and interactive effects of standardization and innovation in developing MC capability and their joint influence on delivery speed. The results will help managers understand the roles of standardization and innovation in improving organizational capability and performance.     

Application of an Analytic Hierarchy Process (AHP) in the GIS interface for suitable fire site selection: A case study from Kathmandu Metropolitan City,Nepal

Kathmandu Metropolitan City, the capital city of Nepal, is prone to different types of disasters. Fire disaster is one of the most recurring in the city. Due to haphazard urbanization, poor fire services, few and old fire engines, insufficient skilled human resources combined with narrow road lanes, clustered households increase the fire vulnerability in Kathmandu Metropolitan City. This paper documents the fire station suitability zonation mapping in Kathmandu Metropolitan City using Group Decision Making Process (GDMP) in the GIS interface. Four different selection criteria factors such as distance from roads, land cover, distance from rivers and population density are considered for analysis and the Analytic Hierarchy Process (AHP) is used for Group Decision Making Process (GDMP). The results reveal that only 13.46% of the study area is highly suitable for fire station location. Hence, the fire station suitability zonation map is trustworthy and can be used for the construction of new fire stations in Kathmandu Metropolitan City.     

A decision model for bank branch site selection: Define branch success and do not deviate

Site selection is one of the most important decision making processes for firms since, if done correctly, it provides access to the best customers and the greatest market potential. In contrast, poor location choices are costly and difficult to reverse.This paper deals with the single branch site selection problem in the banking context. Due to the high level of complexity (several factors have to be taken into consideration in the decision making process as well as a wide range of entities' internal requirements), to date there is no single procedure that fits all needs. This paper attempts to provide a solution to this problem by proposing a unified method based on minimizing the distance from the candidate-branch to the most successful branches, taking into account each banking institution’ notion of branch success. This methodology would work well at the lowest possible cost.     

A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

In uncertain circumstances like the COVID-19 pandemic, designing an efficient Blood Supply Chain Network (BSCN) is crucial. This study tries to optimally configure a multi-echelon BSCN under uncertainty of demand, capacity, and blood disposal rates. The supply chain comprises blood donors, collection facilities, blood banks, regional hospitals, and consumption points. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is suggested to formulate the problem which aims to minimize network costs and maximize job opportunities while considering the adverse effects of the pandemic. Interactive possibilistic programming is then utilized to optimally treat the problem with respect to the special conditions of the pandemic. In contrast to previous studies, we incorporated socio-economic factors and COVID-19 impact into the BSCN design. To validate the developed methodology, a real case study of a Blood Supply Chain (BSC) is analyzed, along with sensitivity analyses of the main parameters. According to the obtained results, the suggested approach can simultaneously handle the bi-objectiveness and uncertainty of the model while finding the optimal number of facilities to satisfy the uncertain demand, blood flow between supply chain echelons, network cost, and the number of jobs created.     

Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors

The WHO goal of eradicating measles is delayed by widespread scepticism of parents against the recommended MMR vaccination. In this context, a model of the prevalence of measles that incorporates behavioural aspects is desirable. Parental decisions can be influenced by epidemiological and behavioural factors. The former include vaccination coverage and its impact on the prevalence of the disease. The latter include perceptions of the risk to be infected, which affects vaccination decisions, as well as government campaigns to affect vaccination behaviour, vaccination scares or changes in disease control policies. We develop a model that incorporates both kinds of effects. In particular, we illustrate how incorporating parental response to a change in the prevalence of the disease impacts the outcome of governmental policies aiming to increase the vaccination coverage. While calibrated to measles, this model is also applicable to other childhood diseases, such as pertussis or diphtheria. Different scenarios illustrate the long-term consequences of the interaction between health policies (in particular, vaccination campaigns) or the agenda of social institutions (e.g., drawing attention to specific events to create vaccination scares) and parental reactions. Periodic ups and downs of the disease's prevalence, characteristic of epidemiological feedback, are the consequence of the interaction between parental behaviour and events such as vaccination campaigns or vaccination scares. International and national health authorities, pursuing the fight against measles, may be helped by the potential of the model to provide understanding in the way different predictors of vaccination behaviour interact.     

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

The high contagion rates of COVID-19 and the limited amounts of vaccines forced public health authorities to develop vaccinations strategies for minimizing mortality, avoiding the collapse of health care infrastructure, and reducing their negative impacts to societies and economies. We propose a Multi Criteria Group Decision Making for prioritizing a set of COVID-19 vaccination alternatives, under a picture fuzzy environment, where the weights for Decisions Experts (DE) and criteria are unknown. A panel of six DEs assess six criteria for prioritizing four groups for vaccination. The weights for DE and criteria are handled in the form of fuzzy sets. Three types of weights are calculated: subjective, objective, and mixture weights.According to our results, three out of the six criteria hold 60% of the strategic importance: 1) allocation and distribution, 2) COVID-19 strains and 3) capabilities and infrastructures. However, persons with comorbidities became the group with the highest priority, followed by essential workers, women, and adults older than 40 years. Governments, decision makers, and policy makers can find rigorous scientific evidence for articulating effective vaccinations campaigns from this work, and contribute to minimize undesired outputs, such as high mortality rates or collapse of hospitals.     

Guest Editorial: A purchasing and supply management view of supply resilience for better crisis response

Purchasing and supply management (PSM) has been under great pressure since the COVID-19 pandemic first shook the world. Companies and public organizations faced new kinds of supply disruptions, and at a scale never seen before. New response abilities were required from PSM to address these challenges and disruptions. This Editorial introduces four articles in the Special Issue on “PSM learning from the pandemic: transforming for better crisis management.” These empirical contributions show how companies could build resilience to survive and be competitive during the COVID-19 pandemic. This Editorial discusses how supply resilience should be conceptualized in post-pandemic supply chains adopting a PSM perspective. We suggest that supply resilience practices should be developed and planned according to whether they strengthen existing supply chain relationships (bridging) or establish new ones (buffering) and whether they are short-term (temporary) or long-term (permanent) orientated. Furthermore, three supply resilience capabilities, absorbing, responding and capitalizing, should be prioritized in supply chains for responding to and recovering from global crises and disruptions. Supply resilience is key to crisis response and recovery, and PSM has an essential role in building and sustaining that resilience.     

How social enterprises manage their organizational identification: a theoretical framework of identity management approach through attraction,selection, and socialization

Abstract

Social enterprises, as a typical type of hybrid-identity organization, face identification tensions among members, arising from the divergent identities. Prior research has focused on how hybrid identities can be managed at the organizational level. However, the process through which identification emerges in hybrid-identity social enterprises remains relatively unexplored. This study addresses these gaps and aims to contribute to identity and identification theory. This research has taken a qualitative (case study) approach, with in-depth interviews and archival data from nine social enterprises in Taiwan. Our findings reveal three different types of responses to hybrid identities of social enterprises: synthesis, integration, and deletion. It is observed that different hybrid identities management and organizational identification management practices will lead to members’ identification and dis-identification. This research proposes an attraction-selection-socialization model, suggesting that, to foster identification, social enterprises need to manage their hybrid organizational identities and embed the new common identity into members’ daily work through attraction, selection, and socialization processes.     

Impact of epidemic outbreaks (COVID-19) on global supply chains: A case of trade between Turkey and China

COVID-19 has negative impacts on supply chain operations between countries. The novelty of the study is to evaluate the sectoral effects of COVID-19 on global supply chains in the example of Turkey and China, considering detailed parameters, thanks to the developed System Dynamics (SD) model. During COVID-19 spread, most of the countries decided long period of lockdowns which impacted the production and supply chains. This had also caused decrease in capacity utilizations and industrial productions in many countries which resulted with imbalance of maritime trade between countries that increased the freight costs. In this study, cause and effect relations of trade parameters, supply chain parameters, demographic data and logistics data on disruptions of global supply chains have been depicted for specifically Turkey and China since China is the biggest importer of Turkey. Due to this disruption, mainly exports from Turkey to China has been impacted in food, chemical and mining sectors. This study is helpful to plan in which sectors; the actions should be taken by the government bodies or managers. Based on findings of this study, new policies such as onshore activities should consider to overcome the logistics and supply chain disruptions in global supply chains. This study has been presented beneficial implications for the government, policymakers and academia.     

A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran

Human Development Index (HDI) is a useful tool for policy makers to understand the degree of development in their societies and set new policies to improve it. Traditionally, the United Nations Development Program (UNDP) releases HDI scores of countries based on the three key dimensions of healthy life, population education and standards of living annually. However, HDI scores have some deficiencies such as methodology, indexes selection and measures time lag. In this paper, a new approach is proposed to calculate semi-HDI scores. First, in each dimension of health, education and standard of living, new and extra criteria are selected. Then, policy makers' preferences are considered to assign the weights of criteria in each dimension using best worst method (BWM). Then, MULTIMOORA method is applied to rank provinces of Iran in each dimension. Finally, the semi-HDI scores of provinces are calculated based on geometric mean of healthy life, population education and living standards. According to the semi-HDI scores, Kohgiluyeh & Boyer- Ahmad and Sistan & Baluchestan provinces are the most and the least developed provinces of Iran, respectively.     

城市产业战略的若干理论及应用--以上海市嘉定区产业定位为例

城市产业的战略定位关系着城市发展的成败,现有产业定位在理论上主要依据比较优势理论(绝对优势论、比较优势论、机会成本说)或比较优势理论的延伸(区域分工理论).事实上,随着全球化进程的推进,跨国公司可以在全球范围内组织资源,原有的基于特殊生产要素的比较优势逐渐衰退,而内涵更广的竞争优势越来越成为决定一个城市发展成功与否的关键.而且现有产业定位研究在对象层面上以区域为主,随着全球化城市网络体系的形成,区域之间的竞争越来越体现为城市之间的竞争,因此对城市产业定位的研究更显重要.文章将对产业定位的已有若干理论进行回顾总结,并引入竞争优势理论、新贸易理论和城市化阶段理论,提出城市产业定位的区域视角、竞争视角、城市化视角等的一般方法.并以上海嘉定的产业定位为例,阐述上述理论的具体实践.     

A data envelopment analysis game theory approach for constructing composite indicator: An application to find out development degree of cities in West Azarbaijan province of Iran

Data envelopment analysis (DEA) model has been widely applied for constructing composite indicator and finding development degree of areas. With the increasing number of indicators, the distinguish power of DEA model is decreased. In this paper, in order to increase distinguish power in DEA model and find out the fair weights in cross-efficiency DEA context, the game theory approach is applied. The DEA-Game theory approach is used to rank cities in West Azarbaijan province of Iran. First, 68 suitable indicators are determined and then, the indicators are classified in 10 sectors. Finally, the actual data for year 2013 is gathered and DEA-Game theory model is applied. To verify and validate the DEA-Game theory approach, simple additive weighting (SAW) and TOPSIS methods are used and the results are compared. The Spearman correlation between DEA-Game, SAW and TOPSIS models shows that the DEA-Game theory model is suitable for constructing the composite indicators.