Analytic hierarchy process : An overview of applications

The Artificial Intelligence field continues to be plagued by what can only be described as ‘bold promises for the future syndrome’, often perpetrated by researchers who should know better. While impartial assessment can point to concrete contributions over the past 50 years (such as automated theorem proving, games strategies, the LISP and Prolog high-level computer languages, Automatic Speech Recognition, Natural Language Processing, mobile robot path planning, unmanned vehicles, humanoid robots, data mining, and more), the more cynical argue that AI has witnessed more than its fair share of ‘unmitigated disasters’ during this time – see, for example [3,58,107,125,186]. The general public becomes rapidly jaded with such ‘bold predictions’ that fail to live up to their original hype, and which ultimately render the zealots’ promises as counter-productive.

Computational Intelligence: An Introduction

Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probable options. The purpose of this article is to systematically review the applications and methodologies of the MCDM techniques and approaches. This study reviewed a total of 393 articles published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinion, these articles were grouped into 15 fields. Furthermore, these articles were categorised based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilising research, MCDM developing research, and MCDM proposing research). The results of this study indicated that in 2013 scholars have published articles more than in other years. In addition, the analytic hierarchy process (AHP) method in the individual tool...

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Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014

Neural networks are used in business organizations for providing intelligent decision support. The ABI/Inform bibliographic database has over 1 000 publications on business-related research in neur...

A bibliometric analysis

http://www.producao.ufrgs.br/arquivos/disciplinas/497_maasen_e_hansen.pdf

An AHP-based approach to ERP system selection

Group decision making in a multiple criteria environment: A case using the AHP in software selection

https://www.computing.dcu.ie/~roconnor/LaiTruebloodAndWong.pdf

Software selection: a case study of the application of the analytical hierarchical process to the selection of a multimedia authoring system

A bibliography of neural network business applications research: 1994–1998

A survey of the application of fuzzy set theory in production and operations management: 1998–2009

Of the multitude of dot-coms in existence in the 1990s, only a fraction survived the crash of the e-commerce (EC) market in the summer of 2000. These companies must now rediscover the principles that governed businesses prior to the EC era. Dot-coms must be rebuilt and transformed to face the new economy: not only must they devise innovative e-strategies [1], but they must also restructure around new business models. After such reengineering efforts, some dot-coms have steadily recuperated from the debacle, but many more are still struggling.Little research has compared the performance of companies with different business types, including B2B, B2C, and non-EC, and explored their endeavors to continue after the EC crash. In this article we report the results of our investigation of EC companies in the aftermath of the crash, with particular emphasis on their performance as compared to their counterpart non-EC companies, and in light of their EC operations experience. We also identify e-strategies introduced by different companies and evaluated their effectiveness by correlating them with company performance, and examine whether this strategy-performance relationship is contingent upon business type.Our study adopted a three-stage data collection method. The first stage involved an analysis of the annual reports of 103 companies listed in the Growth Enterprise Market (GEM), which was established by the Stock Exchange of Hong Kong in November 1999. In addition, 16 EC companies with similar histories, reputations, and backgrounds were included. Although GEM imposes no restrictions on the nature of an applicant's business, many of its listed companies come from IT or EC-related fields. Classification of EC and non-EC companies was based on the Dow Jones Internet Index, which classifies firms as EC companies if they derive more than 50% of revenue from EC activities. The latest reports of these 119 companies were thoroughly analyzed to derive financial indices of performance.

Bo K. Wong

Papers

Group decision making in a multiple criteria environment: A case using the AHP in software selection

Software selection: a case study of the application of the analytical hierarchical process to the selection of a multimedia authoring system

A bibliography of neural network business applications research: 1994–1998

A survey of the application of fuzzy set theory in production and operations management: 1998–2009

Business types, e-strategies, and performance