With the progress in technology and innovation in product development, the contribution of computer- aided design (CAD) software in the design and manufacture of parts/products is growing on significantly. Selection of an appropriate CAD software is not a trifling task as it involves analyzing the appositeness of the available software packages to the unique requirements of the organization. Existence of a large number of CAD software vendors, presence of discordance among different hardware and software systems, and dearth of technical knowledge and experience of the decision makers further complicate the selection procedure. Moreover, there are very few published research papers related to CAD software selection, and majority of them have either employed criteria weights computed utilizing subjective judgements of the end users or floundered to incorporate the voice of customers in the decision making process. Quality function deployment (QFD) is a well-known technique for determining the relative importance of customers’ defined criteria for selection of any product or service. Therefore, this paper deals with design and development of a QFD-based decision making model in Visual BASIC 6.0 for selection of CAD software for manufacturing organizations. In order to demonstrate the applicability and potentiality of the developed model in the form of a software prototype, two illustrative examples are also provided.

Investors’ decision-making are influenced by certain biases as reported in literature. Fundamental analysis is based on the assumption that investors think rationally, but in practice, things may be different. This study captures the impact of herding behavior and overconfidence biases on the investors’ decision-making in Pakistan. The proposed study collects the necessary data through questionnaires distributed among 150 respondents who were active in stock market and manage to process 100 completed ones. The relationships between investors’ decision-making and herding behavior as well as overconfidence biases were empirically tested using Ordinary Least Square (OLS) method. The results show that Pakistani investors’ decisions were significantly influenced by both herding behavior and overconfidence biases.

Making rational decisions in times of uncertainty is an important capability required of marketing managers. However, choosing the precise quantitative decision-making technique or a combination of such tools usually presents managers with a score of challenges. To lessen this challenge, this single case research demonstrates how the choice of three Bayesian decision models (Laplace criterion, Savage minimax regret, and Hurwicz coefficient of realization) can reduce uncertainty in content marketing, search engine optimization (SEO), and referral marketing decision. We employed the case study approach to enable direct access to the decision-making process of the case organization, and to collect relevant data relating to the three marketing decision variables. Results show that, although the Laplace criterion may not have a direct effect on content marketing decisions, it influences the decision-making process leading to the creation and promotion of content. The Savage minimax regret had a direct bearing on SEO decision-making. Hurwicz's coefficient of realization yielded no direct impact on referral marketing but shows the possibility of influencing decision-making processes that led to the development and implementation of referral marketing campaigns. The implications are discussed.

Competitive intelligence is the art of gathering, processing and analyzing the information about the competitors and environment in order to create and sustain the competitive advantage. The application of competitive intelligence in export companies can provide a complete picture of current and future competitive status for managers in addition to obtaining the most appropriate strategic decisions, which could ultimately lead to the improved exports in these companies. This study investigates the role of competitive intelligence for improvement of exports in Iranian industries. Using structural equation modeling, the study has detected six factors including understanding the competitive environment, intelligent response, superior features, customer orientation, managerial skills and competitive advantage.

Flexible manufacturing system (FMS) is an important component of competitive strategy, which could be used for improving organizational performance, productivity, and profitability. The goal of this research is to use DEMATEL approach for finding the intensity of influence of selected criteria. Then, in order to evaluate flexible manufacturing systems, the results of DEMATEL are used in SAW method. A questionnaire was developed and ten professional experts working in various departments of Aluminum Composite Panel Industry are asked to answer its questions. The obtained results reveal that in this case, it is a better choice not to implement and develop FMS.

Six Sigma is a philosophy of unremitting improvement and excellence in all aspects. The concept is a satisfactory modification process tool through customers, continuous improvement and stakeholder participation. Six Sigma is considered as statistical analysis, assessment scales and customer-oriented production accomplishments and it leads to defect production reduction. This paper recommends an approach to select Six Sigma projects using fuzzy multiple attribute decision making techniques composed with another concoction tool. Through insightful quarrying of literature, rudimentary criteria for selecting Six Sigma projects were revealed. The fundamental criteria were identified consuming the fuzzy hypothesis test. Having identified the most indispensable criteria, the weight of criteria were determined. Appling FANP techniques. Having calculated the weights pertinent to criteria through three methods, SAW, TOPSIS, and Fuzzy VIKOR, Six Sigma projects were introduced and prioritized. Applying the three methods engendered various results, which required the application of an amalgamation technique, entitled as Borda and it helped to clarify the final project rate.

Retrofitting technologies have helped to manage energy consumptions in residential, public and industrial buildings. However, understanding of the technical and economic considerations for selection of appropriate retrofitting technology is still evolving and divergent. Thus, this study presents a framework that combines techno-economic requirements as a means for evaluating the important retrofitting criteria and suitable lighting retrofit technologies for building projects. The framework is hinged on the unique features of entropy fuzzy and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods. The analysis of the lighting technology selection was performed from technical, economic and techno-economic perspectives. During the application of the proposed framework, four lighting technologies (CFL, T5, E-ballast and T8-electronic) and nine techno-economic criteria were considered. The most and least important techno-economic criteria for the case study were net present value and electricity saved, respectively. The least and most suitable retrofitting technologies were T8-electronic and CFL, respectively, from techno-economic perspective. T5 and T8-electronic were identified as the most suitable lighting technologies from an economic and technical perspectives, respectively. This discrepancy in the results justified the need for the techno-economic approach for the retrofitting technologies evaluation.

Non-traditional machining (NTM) refers to a variety of thermal, chemical, electrical and mechanical material removal processes, developed to generate complex and intricate shapes in advanced engineering materials with high strength-to-weight ratio. Selection of the optimal NTM process for generating a desired feature on a given material requires the consideration of several factors among which the type of the work material and shape to be machined are the most significant ones. Presence of a large number of NTM processes along with their complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Thus, the objective of this paper is set to develop a decision-making model in Visual BASIC 6.0 to automate the NTM process selection procedure with the help of graphical user interface and visual decision aids. It is also integrated with quality function deployment technique to correlate the customers’ requirements (product characteristics) with technical requirements (process characteristics). Four illustrative examples are also provided to demonstrate the potentiality of the developed model in solving NTM process selection problems.

Social media has grown steadily during the last decade and it is now considered as a new opportunity to use for different purposes such as decision making. The primary objective of this paper is to review articles related to social media and decision making using manual and bibliometrics anal-ysis methods, and to identify top themes in these articles. We have reviewed the papers published between 2008 and the first month of 2019 in Scopus where 1,159 articles were published in this period. These articles come from 733 sources and 3,459 authors. According to our survey, United States is the most productive country. Moreover, most collaborations occurred between two coun-tries of United States and United Kingdom as well as between United States and China. The bibliometrics analysis examines global research in this field from the different point of views.

The way orders are accepted or rejected is the most important factor in customer satisfaction and success of make-to-order systems. The incoming orders to such organizations have certain delivery date in which the customer expects the order to be fulfilled and delivered. In some cases, unexpectedly increased orders exceed the existing capacity for on time fulfillment. In addition to rejection of order, as a typical choice, other options like outsourcing and capacity expansion are available to compensate for capacity shortage and deliver incoming orders according to schedule. However, each of the proposed options is superior in one or more criteria and so selecting the best one is not simply possible. The main goal of this study is to provide managers with a comprehensive, systematic, and applicable approach to evaluate and select the best of the existing options. For this purpose, a model comprised of some multi-criteria techniques is delivered. Our proposed model is a blend of FAHP and FTOPSIS methods. In this model, FAHP is first used to determine the weight of criteria and then Fuzzy-TOPSIS (FTOPSIS) is employed to rank the options. Finally, the proposed model is applied on an actual case to assess and examine its efficiency.