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One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime value (CLV) measured by three purchase variables: “Recency,” “Frequency” and “Monetary.” However, due to the ambiguity of these variables, using deterministic approach is not appropriate. For tackling this matter, the purpose of this paper is to propose a new method of customer segmentation and ranking by combining fuzzy clustering (as a segmentation method) and fuzzy AHP (as a ranking method).

First, customers are classified based on purchase variables using fuzzy c-means clustering algorithm. Second, the variables are weighed applying an optimized version of AHP method. Considering the derived weights and customer groups, this paper follows to ranks segments based on CLV. The developed methodology has been implemented for a large IT company in Iran.

The results show a tremendous capability to the company to evaluate his customers by dividing them into nine ranked segments. The validity of clusters has been submitted.

For researchers, this study provides a useful literature by combining FCM and an optimized version of fuzzy AHP in order to cover the limitations of previous methodologies. For organizations, this study clarifies the procedure of customer segmentation by which they can improve their marketing activities.

Managers can consider the proposed CLV calculation methodology for selling the next best services/products to the group of customers that are more valuable, by calculating the entire lifetime value of the customers.

This study contributes to the process of customer segmentation based on CLV, proposing a new method which covers the limitations of previous customer segmentation methods.

Software-as-a-Service (SaaS) has the potential to provide substantial opportunities for organizations to improve their information technology without cost and management concerns. However, organizations have not utilized it to the desired level because it is very challenging for them to completely transform their basic conventional methods of running software into SaaS as a high-tech method. On the other hand, organizations have doubt which factors should be mostly considered if they want to move to SaaS. Therefore, investigating the adoption of SaaS can contribute organizations to benefit from this technology. The purpose of this paper is to provide a good insight into SaaS technology adoption.

Considering Technology, Organization and Environment (TOE) framework and diffusion of innovation (DOI) theory as the basis, 22 university experts expressed their idea about the proposed model of SaaS adoption. Then, 30 IT professional in 15 IT enterprises that had adopted SaaS were asked to fill the questionnaire related to fuzzy Analytic Hierarchy Process (AHP) based on linguistic preference relations (LinPreRa) in order to rank the submitted criteria.

The findings demonstrate that all attributes of Technology (relative advantage, compatibility, complexity, trialability, observability and security and privacy), Organization (IT resource, sharing and collaboration culture) and environment (competitive pressure, social influence) are influential in the adoption of SaaS. Moreover, the top five influential factors are relative advantage, competitive pressure, security and privacy, sharing and collaboration culture and social influence based on adopter’s opinions.

For researchers, this study provides a useful literature, which can help them in related subject. In addition, it applies IT adoption theories in SaaS context that can be extended in future studies. For organizations, this study derives priority of factors by which they can make strong decisions about adoption of SaaS.

This study contributes to the adoption of SaaS technology using well-known IT adoption theories. A version of Fuzzy AHP based on LinPreRa was used in order to cover the limitations of previous methodologies of ranking the criteria.

The purpose of this paper is to presents an analysis of geographically and disciplinary scattered academic publications of cloud computing (CC) research in information systems. This review aims to understand the research methodology, research frameworks and models, geographical distribution, trends, critical factors and causal relationships associated with cloud computing adoption (CCA).

Systematic-literature-review using natural language processing is conducted to explore the phenomenon. The relevant research studies are extracted from various online databases using quality-assessment-criteria.

The study is a novel attempt to highlight the differences in critical factors for CCA in different country-settings. Further, the research explores the causal relationships among the identified factors. The findings of this 12-year systematic-review contribute by aiding the providers and potential adopters to devise context-specific strategies for the penetration of cloud services and sound adoption decisions (ADs), respectively. The findings also highlight the prospective avenues of research in the domain for researchers. Using the in-depth analysis, conceptual frameworks have been proposed that can assist in exploring the pre-adoption and post-adoption of CC.

This study contributes to CCA research by providing holistic insights into the methodology, research framework and models, geographical focus, critical factors and causal relationships influencing the AD or intention. The review highlights the unexplored emerging research topics in the field of CCA for future research directions.

The present study focuses on the cost of quality (CoQ) based on which organizations can evaluate their quality-related activities in economic terms. The purpose of the study is to identify the CoQ practical implications as well as to group them into logical themes.

A systematic literature review (SLR) was conducted based on well-known academic publishers, such as Emerald Insight, Elsevier/ScienceDirect, SpringerLink, Taylor & Francis, Wiley and Scopus. Sixty-seven peer-reviewed journal articles in the field of CoQ were collected, which were published between 2010 and 2019. The “affinity diagram” was applied to group the practical implications identified into logical themes.

A plethora of CoQ practical implications were identified and grouped into the following meaningful themes: benefits of CoQ measurement, effects of CoQ, business sectors measuring CoQ, factors influencing CoQ measurement, CoQ elements, future research in CoQ and the role of government.

The limited number of the publishers and keywords used to search for the articles of interest, as well as the subjectivity of grouping the large number of the practical implications into themes are the main limitations of the present study. These limitations constitute the basis upon which future literature review studies can be designed.

The present study by presenting analytically and in summary (through the themes revealed) the CoQ practical implications, provides all the respective available literature in a single study for the benefit of practitioners and academics. Thus, clear and straightforward guidelines are given to practitioners with regard to CoQ issues and academics with regard to research topics of high interest.

No previous SLR study focusing on analyzing the practical implications of CoQ has been published so far.