Analisis Preferensi Konsumen Terhadap Produk Sepatu Pada Bisnis Online Menggunakan Conjoint Analysis (Studi Kasus: Grizzlyshoe)

Online business is growing with the application of information technology in marketing and sales. Grizzlyshoe is one of the local online shoe sellers that applies information technology in determining consumer preferences. Consumer preferences are carried out to determine the desired combination of product attributes as a reference for selling shoe products according to consumer desires, so that they can focus on a product based on consumer needs. The purpose of this study is to identify product attributes according to the usability value that arises from each attribute, to identify combinations of product characteristics, and to provide alternative proposed improvements to shoe sales. The method used in data collection is a questionnaire and documentation which includes 105 respondents according to the criteria. The application of the 4P marketing mix is used to determine variables including product, price, place, and promotion, and assign an attribute based on these variables. Conjoint analysis is a method used to determine consumer preferences for several attributes of a product that has been provided and get the desired combination of attributes of a product. The results of the conjoint analysis method in this study obtained stimuli (combinations) of product attributes that the respondents liked were shoes with the Compass brand, hi model, using double box packaging, giving discounts with cashback vouchers, advertising with various marketplaces and sales locations located in crowded environments. namely car free day and exhibition

Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Comparing alignment factors in SMEs and large organizations: a planning integration perspective

Measurement of the alignment between business strategies and information systems (IS) has demonstrated positive impact for the organizational performance. The factors that have proved relevant when assessing the maturity level of alignment are: communication, competency/value measurement, governance, partnership, architecture & scope, and skills. Existing research, however, has focused on the assessment of these factors on large organizations and has barely explored their impact on Small and Medium Enterprises (SME). This paper uses the data provided by 127 participants from large and SMEs in order to identify whether the aforementioned factors are also relevant for assessing the level of alignment maturity in SMEs. The results from this research suggest that there are not significant differences between large organizations and SMEs when assessing those factors. In addition, this research also explored the relation between different planning integration of alignment (independent, sequential and simultaneous) in order to measure the perceived relevance of the factors. The results suggest that the planning integration identified on SMEs and large organizations has a positive correlation on how these factors are ranked. For both SMEs and large organizations where the formulation is simultaneous, the relevance of the factors is higher perceived than it is for those where the formulation is independent or sequential

Profile transformation in mobile technology based educational systems : a thesis presented in partial fulfillment of the requirements for the degree of Master of Information Science in Information Systems at Massey University, Palmerston North, New Zealand

In order to meet the learning needs from various types of students, computer aided education systems try to include new methods to provide personalized education to every student. From the early 1970s, a lot of adaptive educational systems have been created to provide training on a variety of subjects. Combined with the Internet, the adaptive educational systems have become web-based and even more popular. Recently, the development of mobile technology has made the web-based adaptive educational systems accessible through mobile phones. It is necessary that the students can also receive adaptive educational contents on mobile phones. This research project investigated the possible student's preference differences between Personal Computer (PC) and mobile phone, and then proposed a student profile transformation framework to address such differences. This research project conducted two surveys on the student profile transformation between PC and mobile phone. A demo web-based educational system that could be accessed from both PC and mobile phone was also developed for participants of the surveys to give more real and precise responses. Based on Felder-Silverman Learning Style Theory (Felder, 1993; Felder & Silverman, 1988) and the results of the surveys, this thesis proposes a student profile template and a student profile transformation framework, which both fully considered the influences of device capabilities and locations on students' preferences on mobile phones. Furthermore, the proposed framework integrates a solution for unsupported preferences and preference conflicts. By implementing the proposed template and framework, the students' preference changes between PC and mobile phone are automatically updated according to various device capabilities and locations, and then the students can receive adaptive educational contents that meet their updated preferences

Virtual Collaboration in the Online Educational Setting: A Concept Analysis

This study was designed to explore the concept of virtual collaboration within the context of an online learning environment in an academic setting. Rodgers’ method of evolutionary concept analysis was used to provide a contextual view of the concept to identify attributes, antecedents, and consequences of virtual collaboration. Commonly used terms to describe virtual collaboration are collaborative and cooperative learning, group work, group interaction, group learning and teamwork. A constructivist pedagogy, group-based process with a shared purpose, support and web-based technology are required for virtual collaboration to take place. Consequences of virtual collaboration are higher order thinking and learning to work with others. A comprehensive definition of virtual collaboration is offered as an outcome of this analysis. Clarification of virtual collaboration prior to using it as a pedagogic tool in the online learning environment will enhance nursing education with the changes in nursing curriculum being implemented today. Further research is recommended to describe the developmental stages of the collaborative process among nursing students in online education and how virtual collaboration facilitates collaboration in practice

Complexity in the Context of Information Systems Project Management

Complexity is an inherent attribute of any project. The purpose of defining and documenting complexity is to enable a project team to foresee resulting challenges in a timely manner, and take steps to alleviate them.The main contribution of this article is to present a systematic view of complexity in project management by identifying its key attributes and classifying complexity by these attributes. A “complexity taxonomy” is developed and discussed within three levels: the product, the project and the external environment.Complexity types are described through simple real-life examples. Then a framework (tool) is developed for applying the notion of complexity as an early warning tool.The article is intended for researchers in complexity, project management, information systems, technology solutions and business management, and also for information specialists, project managers, program managers, financial staff and technology directors