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E-commerce companies use different types of dark patterns to manipulate choices and earn higher revenues. This study aims to evaluate and prioritize dark patterns used by e-commerce companies to determine which dark patterns are the most profitable and risky.

The analytic hierarchy process (AHP) prioritizes the observed categories of dark patterns based on the literature. Several corporate and academic specialists were consulted to create a comparison matrix to assess the elements of the detected dark pattern types.

Economic indicators are the most significant aspect of every business. Consequently, many companies use manipulative methods such as dark patterns to boost their revenue. The study revealed that the revenue generated by the types of dark patterns varies greatly. It was found that exigency, social proof, forced action and sneaking generate the highest revenues, whereas obstruction and misdirection create only marginal revenues for an e-commerce company.

The limitation of the AHP study is that the rating scale used in the analysis is conceptual. Consequentially, pairwise comparisons may induce bias in the results.

This paper suggests methodical and operational techniques to choose the priority of dark patterns to drive profits with minimum tradeoffs. The dark pattern ranking technique might be carried out by companies once a year to understand the implications of any new dark patterns used.

The advantages of understanding the trade-offs of implementing dark patterns are massive. E-commerce companies can optimize their spent time and resources by implementing the most beneficial dark patterns and avoiding the ones that drive marginal profits and annoy consumers.

The aim of this paper is to identify the criteria that are used for vendor or supplier rating, prioritize these criteria based on the industry inputs and develop a vendor rating model. The data were collected from an Indian start-up working in product development using three-dimensional printing (3DP).

Factors of importance for vendor rating were identified through industry visits, and interacting with the industry experts from the start-up under consideration, substantiated by extensive review of relevant literature. A questionnaire-based survey was carried out to further narrow down the factors important to the industry, prioritizing them with a pairwise comparison analysis as envisaged in the analytical hierarchy process (AHP) technique along with the calculation of consistency ratios. Technique for order preference by similarity to ideal solution (TOPSIS) methodology was further used for data aggregation.

This research brought forward the criteria that are useful for rating vendors or suppliers with reference to 3DP sector.

This paper integrates AHP and TOPSIS to solve a multi-criteria vendor rating problem. The attempt was made to make vendor rating process universal so that it can encompass all the vendors of the firm.

The purpose of this paper is to study the usage and influence of food labels by the young consumers of an emerging market where food labeling regulation is comparatively recent phenomenon.

A purposely developed questionnaire was administered to 300 randomly selected youths of age between 18 and 30 years. The first part of the questionnaire sought information on socio-demographic profile, whereas the second part of the questionnaire had questions related to consumers’ perception of importance, their reading behavior, and their responses on the information content of food labels. Appropriate statistical tools were used to analyze the data.

Results revealed that young Indian consumers attached considerable importance to the food labels and read it before making a final purchase decision. In addition to price, all the product attributes which had implications for the consumers’ health were considered as extremely important by the young consumers. Information regarding different important product attributes can be broadly clubbed in two categories, namely, “product specification” and “product quality.” The final decision to purchase a product based on the food labels varied significantly based on the consumers’ gender, age, food habit, and residential locality.

Nature of study does not allow drawing a conclusion regarding the causal relationship between food labels and consumers’ purchase decisions.

As labeling regulation is a comparatively recent phenomenon in India, study of the usage and influence of food labels on young consumers’ purchase decision, a hitherto not much-studied subject, will contribute significantly to the literature on food labels.

Understanding of the farmers’ buying process is of great economic and strategic relevance for agri-business firms. The purpose of this paper is to explain the extensiveness of the buying process of Indian farmers in their purchase of agri-inputs and discusses its implications for agri-industries.

Four different dimensions of the buying process, namely, buying decision time, number of information sources used, number of evaluated suppliers, and number of conversations with suppliers were used to study the extensiveness of the buying process of the farmers. Responses of 278 farmers were analyzed with the help of mean and frequency distribution, analysis of variance, and Pearson correlation coefficient.

Overall, the extensiveness of the buying process for the frequently purchased inputs was less in comparison to that of the infrequently purchased inputs. However, there were differences in the extensiveness of the buying process for the inputs within the same category. Farmers’ characteristics influenced their buying process and the impact was more evident in case of frequently purchased agri-inputs. All the four dimensions of the farmers’ buying process were found to be positively correlated for most of the agri-inputs.

The farmers’ buying process varies for different agri-inputs and is dependent on the farmers’ characteristics. Firms can use the findings of the study to develop appropriate marketing strategies to broaden their customers’ base and increase sales.

The paper offers an insight into the farmers’ buying process in India and how the farmers behave in different dimensions of the buying process. There are very few studies on the subject carried out in the Indian context.

E-commerce companies use dark patterns to manipulate customer decisions to survive in the crowded online market and make profit. Although some online customers are aware of the dark patterns, they cannot overcome such manipulations. Therefore, the purpose of this study is to identify and model the barriers to overcoming dark patterns using total interpretive structural modeling (TISM).

Barriers to overcoming dark patterns were identified from the extant literature and were validated by a panel of 18 domain experts. In the modeling phase, TISM technique was used to identify the relationships between the barriers and assign priority to the barriers. Finally, the barriers were plotted and classified into three categories.

User unawareness, trust in brands and normalization of aggressive marketing were found to be the highest priority barriers. Whereas, designer bias, user fatigue, short-term user benefits and design complexity were identified as the most challenging barriers because they have least dependence over the other barriers.

Because TISM results are based on the opinion of domain experts, other statistical techniques could be applied for validation.

This study would educate online customers, while assisting online user communities and regulatory bodies to devise strategies to overcome dark patterns. Additionally, business managers could use the study’s findings to encourage designers to embrace ethical design methods as a competitive advantage.

This study contributes to the research as it is first of its kind to examine the link between dark pattern barriers.

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.

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.

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.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

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.

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.

The purpose of this paper is to examine the consumption patterns and attitudes towards soft drinks among Indian youth.

A questionnaire was used to investigate consumption patterns, attitudes, and socio-demographic profiles of college-attending respondents between the ages of 18 and 30. Cluster analysis and factor analysis were undertaken to obtain a better understanding of the attitudes among young consumers towards soft drinks. A logistic regression model was used as a predictor to distinguish between frequent and non-frequent soft drink consumers.

Indian youths preferred diet drinks and fruit juices more than regular soft drinks. Soft drinks were mostly consumed as distinct drinks (not as substitutes) and on specific occasions. Easy availability of soft drinks at the locations closure to consumers was a critical factor in determining consumers’ purchase and consumption level. Attitude towards the utility and nutritional dimensions of soft drinks had a positive and significant influence on the frequency of consumption.

To remain competitive, soft drinks’ companies need to focus more on healthy products and those that are refreshing and relaxing.

Regulating the availability of soft drinks in and around educational institutions will affect consumption of soft drinks and reduce diseases.

Only a few studies investigating consumption patterns and attitudes among Indian youth towards soft drinks. This study attempts to fill the gap.

The technology used by an organization is significantly influenced by the organization’s preferred competitive capabilities. The Internet of things (IoT) is an important technology, which is implemented by most prominent business organizations. The purpose of this paper is to investigate the relationship between an organization’s strategies and the IoT architectures implemented by the organization.

This study has been carried out on primary data collected with the help of a structured questionnaire. The data have been analyzed by statistical techniques like cluster analysis and discriminant analysis through SPSS.

The empirical investigation of data revealed that there is a relationship between organizational strategy and IoT architectures. The three-layered architecture of the IoT is most suitable for caretakers; the three-, four- or five- layered architectures are suitable for marketeers; whereas innovators find it more suitable to use five- or more-layered architecture of the IoT. This paper draws the conclusion based on maximum likelihood rather than using statistical analyses like ANOVA. The idea behind using the maximum likelihood estimate is that there are many subjective parameters in deciding the architectures of the IoT. These subjective parameters are difficult to quantify, so it is not possible to apply ANOVA on these parameters.

This study considers three organizational strategies; the relationship between other organizational strategies and IoT architecture will be studied in future.

This study offers multiple opportunities to practitioners and consulting firms of the IoT to adopt a suitable IoT architecture according to the organizational strategy. This study equips IoT development engineers to select suitable technology for data capturing, data transmission, and data management and access for an IoT architecture.

Although a lot of work has already been done on the architecture of IoT for different industries and businesses, to the best of our knowledge, this is the first study that relates organizational strategies to IoT architectures. This study applies to all the major industry types.

The use of natural resources by organizations has a significant impact on society, resulting in business firms playing a vital role in developing sustainable development. As a result, corporate sustainability has become an integral aspect of a company’s vision and policy in the modern days. Companies issue sustainability reports based on various criteria and metrics, thereby attempting to gain a competitive edge. This study aims to assess and prioritize the numerous factors that influence corporate sustainability performance.

The analytic hierarchy process (AHP) is used to prioritize the identified determinants of corporate sustainability performance based on the literature. Several experts from business and academia were engaged to build a comparison matrix for assessing the various aspects of corporate sustainability performance. As a result, various corporate sustainability determinants were determined and prioritized following an extensive literature review using the AHP.

The most critical component for companies is an economic indicator. Developing environmentally and socially responsible suggestions must be a priority for the organization’s economic performance. Economic performance is believed to be most heavily influenced by innovation and in the other category like environmental and social performance are highly influenced by environment management policies and shareholder responsibility, respectively. Researchers’ findings suggest that to promote sustainability, top executives should devote all of their attention to innovation, environment management policies and shareholder responsibility.

These studies are primarily concerned with developed countries. And, the other fundamental constraint of the AHP study is that the rating scale adopted in the analysis is conceptual. Therefore, pairwise comparisons with a variety of indicators have the potential to introduce bias into the results.

This paper proposes a methodical and operational technique for selecting the ultimate priority of sustainability indicators when it comes to exploiting competitive information on business performance. The paper also recommended sustainability rating technique might be carried out once every six months to improve the overall quality and performance of the organization.

The advantages of adopting and executing corporate sustainability are enormous, and managers must determine whether sustainability is profitable or not. This question prompts further inquiries. For example, what are the numerous critical determinants of corporate sustainability performance? Several scholars throughout the world are looking at it for this reason. As a result, it is essential to comprehend and prioritize the various determinants of corporate sustainability performance.

The purpose of this paper is to develop a progressive damage framework to predict the fatigue life of cord-reinforced rubber composite under cyclic loadings. Special attention has been paid to failure mechanisms, like cord–rubber interfacial debonding, and rubber matrix damage.

The constitutive modeling is based on the continuum damage mechanics (CDMs) and the thermodynamics of irreversible process. The damage in rubber is described by an istropic law, whereas elasto-plastic continuum model has been proposed for cord–rubber interphase layer. The numerical framework is implemented into commercial finite element code Abaqus/Standard via user subroutine (UMAT).

One of the most important findings obtained from reviewing various techniques is that meso-level fatigue damage modeling based on developed framework can simulate competitive damage scenarios, e.g. debonding, delamination or matrix failure.

A systematic framework for predicting failure in cord-reinforced rubber composite is formulated within the context of CDMs that can also be applied for industrial components, such as tires and airsprings.