Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline

An empirical survey: Can green marketing really entice customers to pay more?

This research integrated the Social Cognition Theory and the Engel Kollat Blackwell customers’ purchasing model (EKB model) to synthetically discuss the three kinds of possible relations comprising “does negatively entice”, “does possibly entice” and “does positively entice” between green-marketing and customers’ purchasing and payment, with consideration given to environmental-protection issues. Based on the measured results, the most contributed contention of this research not only utilized three cross-analytical theories consisting of the social cognition theory (SCT) , the Fuzzy theory (FT) and the EKB model, and the novel F-ANP of the MCDM methodology to evaluate the collected data but it also manifested that Green-marketing does possibly entice customers to pay more (GMPECPM). These measured results have distinctly stunned the fundamental assumption in the traditional green-marketing research field that customers were supposed to be willing to pay more for green products and services because they were supporting green initiatives and helping environmental-protection. Further, major future research directions were also briefly demonstrated in this research as (1) the collection data have to be strengthened to gather more empirical customer feedback, corporate management comments, and professional scholars’ reports; (2) enterprises have to resoundingly establish a green-branding initiative after successfully executing green-marketing strategies.Green Marketing (G-marketing); Multiple Criteria Decision Making (MCDM); Analytical Network Process (F-ANP).

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Research on Comprehensive Evaluation of Food Enterprises Websites

The importance of enterprise website to promote enterprise development is becoming more and more attention by the small and medium-sized enterprises. This paper establishes an evaluation index system of food enterprises websites from the perspective of user experience based on the websites localization and the current literature, and uses analytic hierarchy process to determine the weight of each level index, and establishes the fuzzy comprehensive evaluation model of food enterprises websites, and carries out a case study with the evaluation index system. The case study shows that it is reasonable and credible to evaluate the food enterprises websites with analytic hierarchy process and fuzzy comprehensive evaluation

Using Fuzzy TOPSIS and Balanced Scorecard for Kaizen Evaluation

Background: Kaizen is a very important continuous improvement technique; however, measuring kaizen results/benefits have not been clearly and comprehensively addressed by the literature. Objectives: This paper aims to propose a kaizen measuring system by integrating a Balanced Scorecard (BSC) and a Fuzzy Technique for Order Performance by Similarity to Ideal Solution (Fuzzy TOPSIS). Methods/Approach: Three research instruments were distributed to kaizen experts to allocate kaizen benefits into the four BSC perspectives. The best measures of kaizen benefits were determined by employing the Fuzzy TOPSIS technique. Results: The results present a kaizen performance evaluation system where the benefits were allocated into the four BSC perspectives, and the best measure for each kaizen benefit was chosen using fuzzy TOPSIS. Conclusions: The research contributes to the literature by proposing a kaizen measurement system that will pair each benefit of using kaizen with BSC perspectives and measures, thus expanding the advantages of adopting kaizen to any sector or industry

Cross-border E-commerce Risk Evaluation from Sellers’ Perspective

While the development of cross-border e-commerce is flourishing, the associated risk factors should not be underestimated. In this paper, we analyze risk in cross-border e-commerce from the external environment and platform construction to establish a cross-border e-commerce risk evaluation index system from sellers\u27 perspective. Subsequently, the weights of the indicators are calculated on account of entropy weight method, and combined with fuzzy comprehensive evaluation method to construct a cross-border e-commerce risk evaluation model. The results show that the weight of platform risk is more than environmental risk, and the risk level of cross-border e-commerce from sellers\u27 perspective is low. Finally, we attempt to propose some strategies to prevent risks, hoping to provide some theoretical insights into the issue of risk prevention in cross-border e-commerce

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

The influence of technology, environment and user acceptance on the effectiveness of information system project selection using SEM

The selection of the present information system project is difficult because of the many factors that influence it. Information system project should pay attention to the user acceptance, technology and the environment in terms of their influence on the information system project selection.The purpose of this paper is to determine how much influence user acceptance, technology and the environment have on the information system project selection.This research uses data obtained from several ministries and analyzed using SEM (Structural Equation Models).The results found that the technology and the environment affects user acceptance. Moreover, technology and environment affect the effectiveness of the information systems project selection through the mediating effect of user acceptance. User acceptance, tested by the incorporation of usefulness and ease of use, the results are more modest and in line with previous theories. Furthermore, the external environment highly impacts the information system project selection

Business and Information Technology Alignment Measurement -- a recent Literature Review

Since technology has been involved in the business context, Business and Information Technology Alignment (BITA) has been one of the main concerns of IT and Business executives and directors due to its importance to overall company performance, especially today in the age of digital transformation. Several models and frameworks have been developed for BITA implementation and for measuring their level of success, each one with a different approach to this desired state. The BITA measurement is one of the main decision-making tools in the strategic domain of companies. In general, the classical-internal alignment is the most measured domain and the external environment evolution alignment is the least measured. This literature review aims to characterize and analyze current research on BITA measurement with a comprehensive view of the works published over the last 15 years to identify potential gaps and future areas of research in the field.Comment: 12 pages, Preprint version, BIS 2018 International Workshops, Berlin, Germany, July 18 to 20, 2018, Revised Paper