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1 – 10 of over 2000Vibhav Singh, Niraj Kumar Vishvakarma and Vinod Kumar
E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind…
Abstract
Purpose
E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.
Design/methodology/approach
Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.
Findings
Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.
Research limitations/implications
TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.
Practical implications
The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.
Originality/value
Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.
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Betty Amos Begashe, John Thomas Mgonja and Salum Matotola
This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.
Abstract
Purpose
This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.
Design/methodology/approach
The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.
Findings
The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.
Research limitations/implications
This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.
Originality/value
This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.
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Arzu Şen Kılıç, Can Ünal and Ziynet Ondogan
This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement…
Abstract
Purpose
This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.
Design/methodology/approach
In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.
Findings
According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.
Originality/value
In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.
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Abdul Kadir, La Husen Zuada and Muhammad Arsyad
This paper aims to investigate the relationships amongst career patterns, neutrality of the state civil apparatus, and organizational performance of the local government in South…
Abstract
Purpose
This paper aims to investigate the relationships amongst career patterns, neutrality of the state civil apparatus, and organizational performance of the local government in South Konawe District, Southeast Sulawesi Province in Indonesia.
Design/methodology/approach
Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the relationships between variables through direct and indirect influence testing.
Findings
The findings reveal that career patterns influence neutrality and organizational performance. Neutrality of the state civil apparatus in politics mediates career patterns and local government organizational performance. The findings indicate that, first, promotions most significantly influence the organization’s neutrality and performance. Second, demotions have the least influence on the organization’s robustness and performance.
Originality/value
This paper is among the first to examine the relationships amongst career patterns, neutrality, and organizational performance. Recommendations are provided to improve neutrality and organizational performance, that is, the need to increase promotions and reduce demotions.
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Ke Zhang and Ailing Huang
The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user…
Abstract
Purpose
The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.
Design/methodology/approach
To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.
Findings
In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.
Originality/value
This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.
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Wensong Bai, Mikael Hilmersson, Martin Johanson and Luis Oliveira
The authors seek to advance the understanding of small- and medium-sized enterprise (SME) internationalization at the regional level and examine the role of home market…
Abstract
Purpose
The authors seek to advance the understanding of small- and medium-sized enterprise (SME) internationalization at the regional level and examine the role of home market institutions in this process.
Design/methodology/approach
The authors analyze hypotheses with data from SMEs in five country markets and from the Global Entrepreneurship Monitor. A cluster analysis establishes the regional diversification patterns (based on regional diversification scope, speed and rhythm) and a multinomial regression tests the effect of home market institutions on their adoption.
Findings
The results offer a refined picture of SME regional diversification by revealing three patterns: intra-regionally focused firms, late inter-region diversifiers and early inter-region diversifiers. They also suggest that the adoption of these patterns is determined by SMEs' home market institutions.
Originality/value
The authors develop a nuanced understanding of SME internationalization by building upon and expanding the regionalization rationale in the internationalization patterns literature. Additionally, the authors address the acknowledged, yet rarely investigated, country-level determinants of internationalization patterns.
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Shu Fan, Shengyi Yao and Dan Wu
Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural…
Abstract
Purpose
Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.
Design/methodology/approach
This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.
Findings
It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.
Originality/value
The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.
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The purpose of this study is to determine the effect of laser treatment on disperse dye-uptake and fastness values of polyester fabrics. Furthermore, it was aimed to evaluate…
Abstract
Purpose
The purpose of this study is to determine the effect of laser treatment on disperse dye-uptake and fastness values of polyester fabrics. Furthermore, it was aimed to evaluate colors directly over the photos of fabric samples instead of color measuring with spectrophotometer which is thought to be useful in terms of online digital color assessment.
Design/methodology/approach
In this study, 100% polyester (150 denier) single jersey knitted fabrics (weight: 145 g/m2, course density: 15 loops/cm, wale density: 24 loops/cm) were used in the trials. The effect of laser treatments before and after dyeing on color was investigated. Laser treatments were applied to fabrics at different resolutions (20, 25 and 30 dpi) and pixel times (60, 80 and 100 µs) before dyeing. The power of the laser beam was 210 W and the wavelength was 10.6 µm. In order to determine the effect of laser treatment on polyester; FTIR analysis, SEM-EDX analysis and bursting strength tests were applied to untreated and treated fabric samples.
Findings
It was found that treatments with laser have a significant effect on disperse dye-uptake of polyester fibers, and for this reason laser-treated fabrics were dyed in darker shade. Furthermore, it was determined that the samples treated at 30 dpi started to melt and the fabric was damaged considerably, but the fabrics treated at 20 and 25 dpi were not affected at all. Another result obtained regarding the use of laser technology in polyester fabrics is that if some areas of fabrics are not treated with laser and some other areas are treated with laser at 20 dpi 60 µs and 25 dpi 60 µs, it will be possible to obtain patterns containing three different shades of the same color on the fabric.
Originality/value
When the literature is examined, it is seen that there are various studies on the dyeability and patterning of polyester fabrics with disperse dyes by laser technology. As it is known, today color measurement is done digitally using a spectrophotometer. However, when we look at a photograph on computer screens, the colors we see are defined by RGB (red-green-blue) values, while in the spectrophotometer they are defined by L*a*b* (L*: lightness-darkness, a*: redness-greenness, b*: yellowness-blueness) values. Especially when it is desired to produce various design products by creating patterns with laser technology, it would be more useful to show the color directly to the customer on the computer screen and to be able to speak over the same values on the color. For this reason, in this study, the color measurement of the fabric samples was not made with a spectrophotometer, instead, the RGB values obtained from the photographs of the samples were converted into L*a*b* values with MATLAB and interpreted, that is, a digital color evaluation was made on the photographs. Therefore, it is believed that this study will contribute to the literature.
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Claire K. Wan and Mingchang Chih
We argue that a fundamental issue regarding how to search and how to switch between different cognitive modes lies in the decision rules that influence the dynamics of learning…
Abstract
Purpose
We argue that a fundamental issue regarding how to search and how to switch between different cognitive modes lies in the decision rules that influence the dynamics of learning and exploration. We examine the search logics underlying these decision rules and propose conceptual prompts that can be applied mentally or computationally to aid managers’ decision-making.
Design/methodology/approach
By applying Multi-Armed Bandit (MAB) modeling to simulate agents’ interaction with dynamic environments, we compared the patterns and performance of selected MAB algorithms under different configurations of environmental conditions.
Findings
We develop three conceptual prompts. First, the simple heuristic-based exploration strategy works well in conditions of low environmental variability and few alternatives. Second, an exploration strategy that combines simple and de-biasing heuristics is suitable for most dynamic and complex decision environments. Third, the uncertainty-based exploration strategy is more applicable in the condition of high environmental unpredictability as it can more effectively recognize deviated patterns.
Research limitations/implications
This study contributes to emerging research on using algorithms to develop novel concepts and combining heuristics and algorithmic intelligence in strategic decision-making.
Practical implications
This study offers insights that there are different possibilities for exploration strategies for managers to apply conceptually and that the adaptability of cognitive-distant search may be underestimated in turbulent environments.
Originality/value
Drawing on insights from machine learning and cognitive psychology research, we demonstrate the fitness of different exploration strategies in different dynamic environmental configurations by comparing the different search logics that underlie the three MAB algorithms.
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Xichen Chen, Alice Yan Chang-Richards, Florence Yean Yng Ling, Tak Wing Yiu, Antony Pelosi and Nan Yang
Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This…
Abstract
Purpose
Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.
Design/methodology/approach
A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.
Findings
The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.
Practical implications
This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.
Originality/value
This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.
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