The restaurant's menu is considered the primary determinant of a restaurant's profitability and customer satisfaction. This article explores consumers' preferences of restaurant menu measures applied ...during a crisis. Based on pertinent literature review in conjunction with inputs from F&B experts, the researchers identified a list of 6 restaurant menu practices that managers implement during a crisis. The researchers used the Best-Worst Scaling (BWS) method to identify customers' choices for the menu measures. Based on the analysis of survey responses from 568 restaurant customers, the findings demonstrate that menu measures applied during a crisis are perceived differently across the three restaurant categories: fine dining, casual dining, and quick service. The results of this study have not only practical contribution to the case of Lebanon, but they also fill a gap in the knowledge, and extend the existing literature with restaurant consumers' preference of menu measures during a crisis, and provide a list of practices to be implemented by F&B professionals.
This paper aims at assessing the motivational factors that influence the customer’s preferences of Takaful over conventional insurance. The customers’ information about the Takaful products and ...services based on sharia are identified in order to enable them differentiate Takaful and conventional insurance. The research uses mixed method of data collection. This comprises of questionnaires and in-depth interviews with the respondents from four selected Takaful industries in Saudi Arabia. The questionnaires were analysed using simple percentages and for the interviews, thematic analyses were used. Based on the findings of the study, the customer’s preferences on the selection of Takaful over conventional insurance include protection of Takaful product by sharia, support from the government. Similarly, the absence of risk incurred or transferred to participants, funds contributed in the spirit of brotherhood for all members. Moreover, another customer’s preferences is that contributions (tabarru’) are invested in non-interest based capitalization by the Takaful agents and profits are shared according to individual contributions. Based on Takaful, donations are established at the pooling system in line with sharia and they are formed on the bases of sympathy, consciousness of the idea of tabarru’ as well as abstaining from gharar, maysir and riba.
Sustainable product design has captured considerable attention over recent years due to the growing customer demands of sustainability. To improve the environmental performance of products at the ...early stage of product design, a variety of economic, social, and environmental factors, such as manufacturing cost and time, product yield, capacity, customer preferences, and pollutant emissions, have to be taken into account jointly. However, due to the lack of knowledge and ambiguity of customers and experts, some of these factors may contain epistemic uncertainties, overlooking them may lead to an infeasible design. To fill the gap, we propose a new multi-objective optimization-based technique for order preference by similarity to ideal solution (TOPSIS) method to facilitate sustainable product design under epistemic uncertainty. In the proposed method, we develop a fuzzy Mahalanobis–Taguchisystem method to address the epistemic uncertainty of customer preferences on optimization objectives. Meanwhile, we introduce the Me measure to manipulate the epistemic uncertainty of experts’ judgments on process parameters and variables during the manufacturing process. Subsequently, we implement the new TOPSIS method to obtain the optimal design scheme. We provide an example of sustainable substrate design, along with sensitivity analysis scenarios and comparative studies, to elaborate on the performance of the proposed method.
•Epistemic uncertainties from customers and experts are jointly considered.•A new multi-objective optimization-based TOPSIS method is proposed.•A linear optimization model to generate feasible design schemes is established.•The fuzzy Mahalanobis–Taguchi System is developed to tackle the interactions.•A sustainable substrate design is given to demonstrate the merits of the method.
Islamic banks are one of the financial industries affected by the covid 19 pandemic. The inability to pay their obligations to Islamic banks and deposit withdrawals directly impacts the decline in ...customer business. This condition increases the risk of Islamic banks so that the ability of Islamic banks is needed to maintain customer loyalty. This study aims to analyze customer preferences and satisfaction with Islamic banking services during the pandemic.The data analyzed is primary data with 308 Islamic bank customers as respondents. Determination of the sample using the purposive sampling method with the criteria of the management of Islamic social organizations has been a customer since before the pandemic and made transactions during the pandemic. The data analysis uses the Importance Performance Analysis (IPA) method with the Carter approach (Compliance, Assurance, Responsiveness, Tangible, Empathy and Reliability).The results showed that compliance and assurance have a high level of performance with high preferences and satisfaction. Meanwhile, people's preferences are low, and satisfaction is low because their performance is also low in the tangible and reliability aspects. Another finding is that customers have high preferences but low satisfaction because their performance is typical responsiveness, and people have low preferences. Still, high satisfaction lies in the reliability and empathy aspects.
Using spatial panel data comprising a cross section of 1,461 continuously active Airbnb listings obtained from AirDNA, as well as time series data from NYC and Company and the OECD covering the time ...period September 2014 to June 2016, the present study quantifies own price, cross price, and income elasticities of Airbnb demand to New York City within an empirical tourism demand framework. The particular goal of the study is to establish whether the relationship between Airbnb and the traditional accommodation industry is of a substitutional or of a complementary nature. Employing a one-way fixed-effects spatial Durbin model, it can be concluded that demand is price-inelastic for Airbnb accommodation in New York City, which is a luxury good, and that the city's traditional accommodation industry as well as neighboring Airbnb listings are substitutes for the investigated Airbnb listings. The estimation results are robust against several alternative specifications of the regression equation.
•This is the first study modeling Airbnb demand to New York City employing spatial panel data at the listing level.•It investigates if the traditional accommodation industry is a substitute or a complement for Airbnb in this city.•It is also the first study to quantify income elasticities of Airbnb demand.•Demand is price-inelastic for Airbnb accommodation in New York City, which is a luxury good.•The city's traditional accommodation industry and neighboring Airbnb listings are substitutes.
The Purpose of this study is to evaluate the difference between customer preferences and customer attitudes of Islamic Bank in Ex-Banyumas residency of Central Java, Indonesia. It also evaluates the ...most considers attributes in choosing an Islamic bank. Accidental sampling is used in this study with a total of respondents as 100. To observe the difference in customer preferences, the scoring method and Chi-Square analysis are applied, meanwhile, Fishbein’s Attitude model is used to discover the customer attitudes. It is concluded that there is a significant difference in customer preferences on choosing Islamic banks on Ex-Banyumas residency, particularly when it is based on gender and long-period of customer status. It also revealed that customers’ decision in choosing Islamic banks is influenced by service quality. The findings of this study could give valuable input to Islamic bank management in the improvement in their services. This study is explaining the implementation of the Islamic principle in banking operational activities, as in fact the main reason for most customers to get services from the Islamic bank. This study is also enriched the Islamic banking studies in Indonesia.
Research summary
We examine how interactions among a firm's capabilities influence the extent and direction of firm adaptation under conditions of demand‐side change. Our empirical context is the ...U.S. defense industry, within which we study firms receiving defense‐related Small Business Innovation Research (SBIR) awards around September 11, 2001, an event which constituted an exogenous demand‐side shock in which technology‐related preferences of customers were reshuffled. We find that under demand‐side change, preexisting customer relationships have a double‐edged effect: They facilitate “extension‐based” adaptation when interacted with technology capabilities experiencing a decline in customer preferences, and they hinder “novelty‐based” adaptation when interacted with technology capabilities experiencing an increase in such preferences. We also find that both types of technological capabilities together facilitate adaptation along the extension and novelty paths.
Managerial summary
Demand‐side change, in which customer preferences for particular technologies are reshuffled, occurs in many industry settings. A deeper understanding of the factors shaping firm adaptation under this form of change can influence managers' decisions to implement strategies to plan for and react to such change. Using a sample of firms receiving defense‐related SBIR awards around September 11, 2001, we show that the customer relationships a firm develops prior to demand‐side change can have a double‐edged effect on firm adaptation. Such relationships facilitate “extension‐based” adaptation when combined with technology capabilities declining in customer preferences and hinder “novelty‐based” adaptation when combined with technology capabilities increasing in customer preferences. In addition, the combination of the two technological capability types facilitates adaptation along both paths.
•This method jointly optimizes the selection of product variety, module variants, and personalized module configurations.•Cost-effective product personalization uses continuous optimization of ...parameters and discrete selection of module combinations.•Customer personalization preference data are simulated based on a multivariate normal mixture model of customer preferences.
Open product architecture is a key enabler for product personalization, as it allows the integration of personalized modules in a product architecture to satisfy individual customer needs and preference. A critical challenge for integrating personalized modules into a product architecture is determining the optimal assembly architecture when considering market expectations and manufacturing constraints. In this paper, an optimization method is proposed for determining the personalized product design architecture that incorporates individual customer preferences. First, a decision hierarchy is presented to describe the integrated design decisions of the product architecture, including product variety determination, module variant selection, and personalized module configuration. Next, a profit model is formulated as an overall performance metric that incorporates customer preferences and manufacturing cost. The systematic patterns and randomness of diverse customer preferences are modeled by combining conjoint analysis and market segmentation with a multivariate normal mixture model. Individual customer product utilities in the target market and their product purchase intent probability are estimated through Monte-Carlo simulation, which is incorporated into the profit calculation. Manufacturing limitations on processes and materials are included as they influence manufacturer’s planning on candidate module variants and production strategies of personalized modules. These models are used to determine a product family architecture that maximizes profit by optimally determining its offering of product variants, module combinations, and personalized module configuration through a genetic algorithm. The proposed method is demonstrated by a personalized bicycle architecture design example.
Competitive intelligence uses information collected about competitors to derive better managerial insights. In this study, we focus on identifying the competitors and detecting the competitive ...dimensions concurrently. To achieve this goal, we propose an aspect-level competitive attribution model (a variation of the topic model) to leverage consumer-reviewed products and their review texts. To better analyze product relations and the underlying competitive aspects, we consider consumer limited attention when modeling consumers' preferences and introduce a background aspect to filter out the trivial and maintain the valuable competition-related information in review texts. We validate this approach using a dataset of 785 products reviewed by 15,669 consumers in the auto industry. Based on the empirical experiments, we show that our model can accurately infer high-quality competitive segments and decipher competition-related aspects corresponding to these segments. To highlight differences, we conduct comparisons and find our approach outperforms the benchmark models meaningfully in the literature when predicting consumers' online behaviors.
•We identify the competitors and detect the competitive dimensions concurrently.•We propose an aspect-level competitive attribution model to leverage consumer-reviewed products and their review texts.•We validate this approach using a dataset of 785 products reviewed by 15,669 consumers in the auto industry.
Previous studies have concluded that there are significant differences in travelers’ preferences depending on the trip type. The problem of extracting users’ preferences from a corpus of text can be ...solved by using traditional clustering algorithms, which work quite well when there is no predefined data structure. However, in this paper, we consider the problem of extracting users’ preferences when they belong to a finite number of classes represented by the trip type. In this paper, we propose an encoding method based on a Convolutional Neural Networks (CNNs), trained as a classifier for the classes that predefine data structure. The intuition behind convolutional neural encoding is its ability to maximize the distance between documents belonging to different classes in the new, derived feature space. Findings reveal that CNNs encoding has better discriminative properties than alternative encoding methods such as Latent Dirichlet Allocation or average word2vec encoding. Moreover, we demonstrate that CNNs encoding can be used to identify the unique topics associated with the predefined data structure determined, in this case, by the four trip types.
PDF
