Assessing the factors affecting implementation of unmanned aerial vehicles in Indian humanitarian logistics: a g-DANP approach

Purpose The purpose of this paper is to analyze the factors affecting the implementation of unmanned aerial vehicles (UAVs) in Indian humanitarian logistics. The factors listed are significant as they are hindering the incorporation of this new technology into the humanitarian supply chain, thus creating inefficiencies in the humanitarian logistics sector. Design/methodology/approach This research is approached using a two-step process. In the first step, the particular barriers for UAV implementation are determined by a literature review and consultation with experts. Next, the proposed framework, a combination of grey-decision-making trial and evaluation laboratory (grey-DEMATEL) and analytic network process (ANP), i.e. g-DANP, is used to determine a hierarchical structure for the factors and sub-factors. The grey hypothesis provides sufficient analytical data to an otherwise lacking DEMATEL technique. Also, the use of ANP gives weightage to each factor, allowing us to categorize their importance further. Findings This study reveals that factors like expensive commercial solutions and high transport energy costs are significant factors of the “cause” group, whereas the uncertain cost for maintenance and repair and deficiency of high-level computing are crucial factors of the “effect” category. The mentioned factors, along with many others, are the main reasons for the delayed incorporation of UAVs in humanitarian logistics. Practical implications The results of this study present insights for humanitarian supply chain managers, UAV producers and policymakers. Those in the humanitarian logistics sector can use the findings of this study to plan for various challenges faced as they try and implement UAVs in their supply chain. Originality/value This research is unique as it analyses the general factors hindering the implementation of UAVs in Indian humanitarian logistics. The study enriches existing literature by providing an analytic approach to determine the weightage of various interrelations between the identified factors affecting UAV incorporation in the humanitarian supply chain.

Studying the appointment scheduling window considering patient no-show behavior in one public and one private outpatient clinics

Purpose This study is carried out in one public and one private health-care centers based on different probabilities of patient’s no-show rate. The present study aims to determine the optimal queuing system capacity so that the expected total cost is minimized. Design/methodology/approach In this study an M/M/1/K queuing model is used for analytical properties of optimal queuing system capacity and appointment window so that total costs of these cases could be minimized. MATLAB software version R2014a is used to code the model. Findings In this paper, the optimal queuing system capacity is determined based on the changes in effective parameters, followed by a sensitivity analysis. Total cost in public center includes the costs of patient waiting time and rejection. However, the total cost in private center includes costs of physician idle time plus costs of public center. At the end, the results for public and private centers are compared to reach a final assessment. Originality/value Today, determining the optimal queuing system capacity is one of the most central concerns of outpatient clinics. The large capacity of the queuing system leads to an increase in the patient’s waiting-time cost, and on the other hand, a small queuing system will increase the cost of patient’s rejection. The approach suggested in this paper attempts to deal with this mentioned concern.

A multi-objective model for sustainable closed-loop supply chain of perishable products under two carbon emission regulations

Purpose This paper aims to minimize the total carbon emissions and costs and also maximize the total social benefits. Design/methodology/approach The present study develops a mathematical model for a closed-loop supply chain network of perishable products so that considers the vital aspects of sustainability across the life cycle of the supply chain network. To evaluate carbon emissions, two different regulating policies are studied. Findings According to the obtained results, increasing the lifetime of the perishable products improves the incorporated objective function (IOF) in both the carbon cap-and-trade model and the model with a strict cap on carbon emission while the solving time increases in both models. Moreover, the computational efficiency of the carbon cap-and-trade model is higher than that of the model with a strict cap, but its value of the IOF is worse. Results indicate that efficient policies for carbon management will support planners to achieve sustainability in a cost-effectively manner. Originality/value This research proposes a mathematical model for the sustainable closed-loop supply chain of perishable products that applies the significant aspects of sustainability across the life cycle of the supply chain network. Regional economic value, regional development, unemployment rate and the number of job opportunities created in the regions are considered as the social dimension.

Synergistic effect of R&D and exports on performance in US manufacturing industries: high-tech vs low-tech

Purpose This study aims to explore the strategic impact of R&D and export activity on the diverse dimensions of US manufacturing firms’ performance. It also explores, using a predictive analytic model, the interactive synergistic effect that R&D and exports have on firm performance. Design/methodology/approach This study presents an innovative two-stage regression-neural network approach. Complementing conventional statistical analysis, the predictive backpropagation neural network explores the relative impact of R&D and exports and their synergistic effect on firm performance. Findings This study demonstrates the significant and positive effect of R&D and export strategy/activity on the economic performance of leading US manufacturing firms, particularly on their market-based performance (i.e. sustained growth rate or SGR). Furthermore, this study finds that the synergistic effect of R&D and exports on short-term performance (i.e. return on investment) is positive in high-tech firms but negative in low-tech firms. However, the synergistic effect on SGR is increasingly positive regardless of the level of technology. Originality/value In addition to traditional statistical analysis, this study uniquely investigates the relative importance of selected strategic variables, along with R&D and export activity and their differential synergistic effects, for firms’ economic performance in contrasting industry settings (high-tech vs low-tech).

How to decode the value-consequence-attribute relationship: the application of TISM and ANP techniques

Purpose This paper aims to facilitate positioning strategy formation by decoding the relationship between consumers’ desired values, service attributes and expected consequences. Design/methodology/approach Key informant depth interviews are followed by a questionnaire of self-cause-and-effect assessments. Total interpretive structural modeling (TISM) is used to identify hierarchical structures via pair-wise preference comparisons. The analytic network process (ANP) is used to compute relative weights to evaluate the overall image of identified alternatives. The feedback feature in the ANP is enabled to obtain objective assessments. Findings With the help of both TISM and ANP techniques, the hierarchical and interactive relationships among consumers’ desired values, expected consequences and service attributes are revealed in the context of international airline services. Research limitations/implications The approach presented can help organizations to identify which attributes influence consumer evaluations of a company/brand; obtain the hierarchical and interactive relationships among service attributes, expected consequences and desired values; assess consumer preferences toward identified service attributes; and obtain an objective assessment of the competitive landscape, which can facilitate the development of effective positioning strategies and associated tactics. Practical implications Organizations adopting the methods presented in this study can have a better understanding of the consumer value chain and deliver better customer experiences. Originality/value The current study provides an innovative application of the TISM in conjunction with a feedback-enabled ANP technique to address brand positioning challenges. Future studies may consider adopting the TISM-ANP method as a foundation whenever one attempts to explore the values-consequences-attributes hierarchy.

Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

Market efficiency and price risk management of agricultural commodity prices in India

Purpose Market efficiency leads to transparent and fair price discovery of commodity markets, thus enhancing the value chain for competitive benefit. The purpose of this paper is to investigate the market efficiency of Indian agricultural commodities at spot, futures and mandi markets apart from exploring price risk management in these markets. Design/methodology/approach This study uses Johansen co-integration, vector error correction model and granger causality for analyzing market efficiency of the nine most liquid agricultural commodities across three markets, namely, spot, futures and mandi. All these nine commodities are traded on National Commodity and Derivatives Exchange. Findings The statistical results indicate price discovery exists in the mandi market and spot market leading to futures prices. Mandi price returns are seen to negatively influence futures returns in the case of cotton seed, guar seed and spot returns in the case of jeera, coriander and chana. For castor seed, the three markets are seen to have no long run relationship. The results of Granger causality reveal short run relationship between all the three markets in the case of soybean seed and coriander. In these commodities, prices in all three markets are capable of predicting the prices in the other markets. For the case of cottonseed, Rape Mustard seed, jeera, guar seed, the results indicate unidirectional causality between the mandi markets and the other two markets. Research limitations/implications These results shall facilitate policymakers to explore intervention through integrated agri-platform (IAP) in price discovery and market efficiency. Practical implications The results of this study are useful in understanding the price discovery of mandi markets and its role in the spot and futures market. Agricultural commodities price discovery depends upon the integration of all these three markets. Introduction of IAP as described in the paper shall facilitate price risk management apart from improving the efficiency of price discovery. Originality/value To the best of the knowledge, this is the first study considering mandi, spot and futures prices in the price discovery process in India. In addition, this study found the role of mandi markets in serving the economic function of price discovery and price risk management. Hence, suggests for policy intervention for Indian agricultural commodities to manage price risk.

Evaluation of the components of intelligence and greenness in Iranian ports based on network data envelopment analysis (DEA) approach

Purpose Creating green ports, while observing international and international standards and maritime conventions and regulations and moving toward smart ports, can increase the speed of goods transfer, enable the tracking of ships and goods, increase the transparency of statistics, increase the quality and capacity of ports and reduce costs. Hence, the purpose of this study the development and evaluation of ports play a key role in their commercial success. Development policies can be formulated for these ports by properly evaluating their performance indicators. On the other hand, traditional methods of performance evaluation cannot provide a good multidimensional evaluation of the status of ports. Design/methodology/approach More than 90% of the world’s heavy transit today is carried out by the sea. With this volume of freight, transit accidents are inevitable for ships passing through oceans, seas, waterways, rivers, ports and mooring at docks. Besides, gases from ships’ fuels at sea, especially in ports, oil spills due to maritime incidents, the negligence of the ship’s crew, the use of port equipment, dirty fuel of diesel power substations, etc., have increased greenhouse gases, polluted the environment and endangered human lives. Findings A new approach has been introduced in the field of port performance evaluation based on the components of greenness and intelligence. This approach performs evaluations in two stages and a network. In this study, the performance of 11 Iranian ports was evaluated based on the network data envelopment analysis approach in 2 stages of greenness and intelligence during 4 years. The results indicated that only 5% of the ports meet the standards of intelligence and greenness. Originality/value On the other hand, as shown in the above studies, the issue of green ports is directly related to the development of animal and plant ecosystems in the seas and the environment around ports. The presence of pollution in the ports has caused the animal and plant habitats around the ports to face a complete pollution crisis or to be completely destroyed. Therefore, the development of green port concepts in third world countries will help prevent environmental pollution of the seas. Therefore, it is necessary for ports to review their strategic maritime transport model and use the development of green port indicators in their implementation processes. Therefore, the strategic development of green ports is created to create and benefit from the components of intelligence, and as mentioned in previous research, intelligence and greenness are in line and the lack of development of one of the concepts causes defects in others. According to reports provided in Iran’s maritime transport systems, most accidents have led to environmental disasters during the absence of intelligent equipment. The use of smart technologies prevents all environmental damage and the development of port services. On the other hand, in evaluating the published articles in the field of development of green and smart ports, so far, the components of intelligence and greenness have not been evaluated and analyzed in a practical and operational way in ports and only the influencing the development of agents on each other has been done (Chen, 2019). Therefore, evaluating the efficiency of ports based on green components and intelligence causes ports to fundamentally review their executive infrastructure and take an active part in the global green development plan.

Mining numerical measure of consumers’ product evaluation expressed in words based on latent Dirichlet allocation

Purpose It has always been a hot topic for online retailers to obtain consumers’ product evaluations from massive online reviews. In the process of online shopping, there is no face-to-face interaction between online retailers and customers. After collecting online reviews left by customers, online retailers are eager to acquire answers to some questions. For example, which product attributes will attract consumers? Or which step brings a better experience to consumers during the process of shopping? This paper aims to associate the latent Dirichlet allocation (LDA) model with the consumers’ attitude and provides a method to calculate the numerical measure of consumers’ product evaluation expressed in each word. Design/methodology/approach First, all possible pairs of reviews are organized as a document to build the corpus. After that, latent topics of the traditional LDA model noted as the standard LDA model, are separated into shared and differential topics. Then, the authors associate the model with consumers’ attitudes toward each review which is distinguished as positive review and non-positive review. The product evaluation reflected in consumers’ binary attitude is expanded to each word that appeared in the corpus. Finally, a variational optimization is introduced to calculate parameters mentioned in the expanded LDA model. Findings The experiment’s result illustrates that the LDA model in the research noted as an expanded LDA model, can successfully assign sufficient probability with words related to products attributes or consumers’ product evaluation. Compared with the standard LDA model, the expanded model intended to assign higher probability with words, which have a higher ranking within each topic. Besides, the expanded model also has higher precision on the prediction set, which shows that breaking down the topics into two categories fits better on the data set than the standard LDA model. The product evaluation of each word is calculated by the expanded model and depicted at the end of the experiment. Originality/value This research provides a new method to calculate consumers’ product evaluation from reviews in the level of words. Words may be used to describe product attributes or consumers’ experiences in reviews. Assigning words with numerical measures can analyze consumers’ products evaluation quantitatively. Besides, words are labeled themselves, they can also be ranked if a numerical measure is given. Online retailers can benefit from the result for label choosing, advertising or product recommendation.

A model to reduce the risk of project selection utilizing data envelopment analysis

Purpose Project selection management is a matter of challenge for project-oriented organizations, particularly, if the decision-makers are confronted with limited resources. One of the main concerns is selecting an optimal subset that can successfully satisfy the requirements of the organization providing enough resources to the best subset of the project. The projects for which there are not enough resources or those requiring whole resources of the organization will collapse soon after failed to success. Therefore, the issue is in the risk of choosing a set of projects so that can make a balance in investment versus on collective benefit. Design/methodology/approach A model is presented for project selection and has been tested on the 37 available projects. This model could increase the efficiency of the whole subset of the project significantly in comparison to the other model and it was because of choosing a diverse subset of projects. Findings Provides a general framework for project selection and a diverse and balanced subset of projects to increase the efficiency of the selected subset. Also, reduces the impact of uncertainty risk on the project selection process. Research limitations/implications For the purposes of project selection, any project whose results are uncertain is a risky project because, if the project fails, it will reduce combined project value. For example, a pharmaceutical company’s R&D project is affected by the uncertain results of a specific compound. If the company invests in different compounds, a failure with one will be offset by a good result on another. Therefore, with selecting a diverse set of projects, this paper will have a different set of risks. Originality/value This paper discusses the risk of selecting or being responsible for selecting a project under uncertainty. Most of the projects in the field of project selection generally consider the risks facing the projects or existing models that do not take into account the risk.