Product Customer Research Articles

Importance of Customer Service Channels, Services, and Products in Financial Culture

In this context where we live, equal access and participation of young people to financial services is a pending agenda. This research aims to determine financial inclusion's influence on higher education students' financial culture. This research is carried out under the parameters of the positivist paradigm with a non-experimental cross-sectional design. It was necessary to apply non-probabilistic convenience sampling to collect the data, obtaining 920 respondents. On the other hand, the exploratory and confirmatory analysis was carried out to find the factorial structure of the constructs. Furthermore, to test the proposed theoretical model, applying the methodology of structural equations was necessary. The results indicate an influence between the study variables, obtaining a ?= 0.855 and a p-value of 0.000. Besides, financial products influence financial culture with a ?= 0.331 and a p-value of 0.000), financial services in financial culture with a ?= 0.321 and a p-value of 0.000, and customer service channels in financial culture with a ?= 0.279 and a p-value of 0.000.
 
 Received: 11 November 2023 / Accepted: 28 January 2024 / Published: 5 March 2024

Enhancing sustainability in mass customisation of consumer electronics with salvage value through supply chain financing

ABSTRACT The consumer electronics industry is crucial in the global shift toward sustainability. To meet customers’ personalised needs efficiently and reduce production costs, electronic product suppliers increasingly focus on Mass Customization (MC) and modular production. Implementing a buyback policy for unsold module products with salvage value is a sustainable practice that reduces waste. This study explores two buyback support financing tools to enhance sustainability in the industry, enabling successful MC production. We also investigate how the salvage value based on modularity level and the buyback policy impact operational and financing decisions in the Mass Customization Supply Chain (MCSC). The research reveals that a higher modularity level positively impacts supplier’s profits and optimal capacity levels under both financing strategies. Consequently, this study offers valuable insights into elevating sustainability practices and optimising operational and financing decisions in the context of MC within the consumer electronics industry.

Software and Architecture Orchestration for Process Control in Industry 4.0 Enabled by Cyber-Physical Systems Technologies

In the context of Industry 4.0, this paper explores the vital role of advanced technologies, including Cyber–Physical Systems (CPS), Big Data, Internet of Things (IoT), digital twins, and Artificial Intelligence (AI), in enhancing data valorization and management within industries. These technologies are integral to addressing the challenges of producing highly customized products in mass, necessitating the complete digitization and integration of information technology (IT) and operational technology (OT) for flexible and automated manufacturing processes. The paper emphasizes the importance of interoperability through Service-Oriented Architectures (SOA), Manufacturing-as-a-Service (MaaS), and Resource-as-a-Service (RaaS) to achieve seamless integration across systems, which is critical for the Industry 4.0 vision of a fully interconnected, autonomous industry. Furthermore, it discusses the evolution towards Supply Chain 4.0, highlighting the need for Transportation Management Systems (TMS) enhanced by GPS and real-time data for efficient logistics. A guideline for implementing CPS within Industry 4.0 environments is provided, focusing on a case study of real-time data acquisition from logistics vehicles using CPS devices. The study proposes a CPS architecture and a generic platform for asset tracking to address integration challenges efficiently and facilitate the easy incorporation of new components and applications. Preliminary tests indicate the platform’s real-time performance is satisfactory, with negligible delay under test conditions, showcasing its potential for logistics applications and beyond.

Faktor-Faktor yang Mempengaruhi Customer Satisfaction dan Dampaknya terhadap Habits dan Intention to Revisit Kembali di Industri Kedai Kopi Tuku

<p><em><span>This research aims to investigate the influence of Brand Awareness, Brand Image, Perceived Service Quality, Perceived Product Quality, Physical Environment, Customer Satisfaction, and Customer Habits on Intention to Revisit. The data was obtained through a survey involving the participation of 300 respondents. The researcher utilised primary data obtained by distributing questionnaires randomly through WhatsApp, Instagram, and other social media platforms using Google Forms. The sampling technique employed was non-probability sampling. The sampling technique used in this study is non-probability sampling. The respondents for this research consist of consumers of the Toko Kopi Tuku brand from the X, millennial, and Z generations who reside in the Jabodetabek area. In this study, a variance-based structural equation modelling approach was employed using Smart PLS (Partial Least Square) version 3.2.9 software. The study’s results explored the influence of Brand Awareness, Brand Image, and Perceived Product Quality on Customer Satisfaction, except for Perceived Service Quality and Physical Environment, which did not affect Customer Satisfaction. Customer Satisfaction also influences Customer Habits and Intention to Revisit. Similarly, Customer Habits affect Intention to Revisit. This study has contributed to the research on variables influencing Customer Satisfaction, Customer Habits, and Intention to Revisit</span><span lang="IN">. </span></em></p>

FMCG Industry Customer Segmentation for Cosmetic Product at PT. Paragon Technology and Innovation


 Paragon Technology and Innovation is an Indonesian company within the Fast-Moving Consumer Goods (FMCG) industry that produces cosmetic products. PT Paragon is currently planning to develop new product and need understand further what product shall be prioritized to develop. Customer segmentation could be applied to give initial guide to determine which product to develop first. It is a process that divides customers into groups to find out the characteristics, behavior, or needs of customers for a product. Customer segmentation needs to be conducted because it can be used as supporting data to find out customer characteristics and determine effective and efficient marketing strategies for the company. Segmentation is one of the strategies to face business competition, to retain customers, and to assist management in developing marketing strategies to increase sales and company growth. The purpose of this study is to categorize the customers of PT Paragon Technology and Innovation products based on their characteristics. To determine customer segmentation can be done using the K-Means clustering algorithm. The clustering process is carried out by grouping PT Paragon's customer transaction history data in 2023 in November based on four categories, namely Face Care, Hair Care, Body Wash, and Make Up. The data is analyzed using IBM SPSS to determine the characteristics of each cluster. The population and samples used in the research were 79 and 52. The number of clusters used was 5, namely cluster 1 or struggling man customers, cluster 2 or beauty enthusiast customers, cluster 3 or forever young customers, cluster 4 or beauty careless casual customers and cluster 5 or luxtomer. The main cluster that provides shared value for PT Paragon Technology and Innovation consumers is cluster 2 or beauty enthusiast customers. The main category for shared value is the make up category, referring to the result, we recommend PT Paragon to mainly developa product following that category.

SPECIFICS OF IMPLEMENTING SMART MANUFACTURING IN INDUSTRIAL SMALL AND MEDIUM-SIZED ENTERPRISES: BENEFITS AND LIMITATIONS

Purpose. The aim of the article is to determine the mechanisms for solving the technological and technical limitations of data management during the automation of the production process at industrial enterprises, as well as the economic advantages and limitations created by the introduction of smart production at small and medium-sized industrial enterprises. Methodology of research. The theoretical and methodological basis of the research is the scientific works of leading scientists and practicing entrepreneurs regarding the features and technology of implementing smart production at industrial enterprises. The following general scientific methods were used in the research process: comparison – to study the approaches of the largest producing countries to the management and stimulation of the development of smart production; analysis and synthesis – to analyse the state of implementation of smart production at small and medium-sized industrial enterprises; abstract and logical – for expressing own assumptions and formulating conclusions, graphic – for visual illustration of the conceptual model of optimization of software and hardware of SMEs for data processing of enterprises. Findings. It has been established that the leading technologies forming the system of smart production - the industrial Internet of Things, neural networks based on artificial intelligence and blockchain technology – solve the following technological limitations that existed under the centralized server infrastructure: infrastructure overload due to the increase in the consumption of computing resources (solved as a result of optimization the speed of transaction accounting due to the introduction of artificial neural networks based on artificial intelligence); problems of stakeholder authentication and platform compatibility (solved as a result of automating registration of participants, transactions and as a result of automating the execution of transactions due to smart contracts within the framework of open blockchain technology); insufficient integrity and confidentiality of the data register as a result of compatibility and authentication problems (solved due to the technology of distributed accounting of transactions (blockchain), which allows to avoid falsification of data). It was found that the main economic advantage as a result of the implementation of the mentioned technologies within the framework of the smart production system is the possibility of mass customization of production at the level or almost at the level of the costs of standard mass production. It is specified that these technologies are appropriate for implementation by high-tech industrial enterprises producing products with high added value. Originality. The theoretical aspects of establishing direct and indirect economic benefits from the implementation of a smart production system at industrial small and medium-sized enterprises, approaches to optimizing production in the direction of product customization have gained further development. Practical value. Formulated approaches and recommendations for solving problems related to data processing during the automation of the production process - as a set of technological limitations, as well as an approach for solving technological limitations for the manufacture of customized products can be used at innovation-oriented industrial enterprises, in particular, medium and small ones. Key words: smart production, small and medium enterprises, industrial Internet of things, artificial intelligence, blockchain technology, automation, production, data processing.

Understanding the consolidation mechanism of selective laser sintering/powder bed selective laser process of ceramics: Hydroxyapatite case

PurposeThe consolidation process and morphology evolution in ceramics-based additive manufacturing (AM) are still not well-understood. As a way to better understand the ceramic selective laser sintering (SLS), a dynamic three-dimensional computational model was developed to forecast thermal behavior of hydroxyapatite (HA) bioceramic.Design/methodology/approachAM has revolutionized automotive, biomedical and aerospace industries, among many others. AM provides design and geometric freedom, rapid product customization and manufacturing flexibility through its layer-by-layer technique. However, a very limited number of materials are printable because of rapid melting and solidification hysteresis. Melting-solidification dynamics in powder bed fusion are usually correlated with welding, often ignoring the intrinsic properties of the laser irradiation; unsurprisingly, the printable materials are mostly the well-known weldable materials.FindingsThe consolidation mechanism of HA was identified during its processing in a ceramic SLS device, then the effect of the laser energy density was studied to see how it affects the processing window. Premature sintering and sintering regimes were revealed and elaborated in detail. The full consolidation beyond sintering was also revealed along with its interaction to baseplate.Originality/valueThese findings provide important insight into the consolidation mechanism of HA ceramics, which will be the cornerstone for extending the range of materials in laser powder bed fusion of ceramics.

Navigating Data-Driven Decisions in E-Commerce

Data-driven decision-making has become a critical strategy for e-commerce businesses in the digital age. By leveraging data and analytics, e-commerce companies can gain valuable insights into customer behavior, optimize product offerings, personalize marketing campaigns, and streamline operations. This paper explores the key components of the data-driven decision-making landscape in e-commerce, highlighting the importance of customer insights, product optimization, personalized marketing, and inventory management. It also addresses the challenges organizations face when transitioning to a data-driven culture and provides a framework for successfully navigating this landscape to drive growth and stay competitive.

A new demand function graph: Analysis of retailer-to-individual customer product supply strategies under a non-essential demand pattern.

The core objective of a successful product supply strategy is to determine the mechanism through which consumers' psychological effects influence customer demand. As stated in the theory of supply and demand, a higher level of dynamic equilibrium should be formed in which demand drives supply and supply creates demand. There is a lack of systematic research in the literature on the identification of consumer goods demand attributes and the formation of influencing factors in consumer goods supply chains. In this paper, we use the literature on demand functions and product pricing functions to establish three mathematical models to study the factors that influence retailers in designing and planning product supply strategies for different customers under nonessential demand patterns and to solve the profit maximization problem. The results of numerical examples validate the validity of the model. The research results can help retailers develop different supply strategies according to different types of customers and different demand patterns, thereby improving business performance. The theoretical contribution of this study is the construction of value ranges and a demand function diagram for identifying consumer product demand attributes.

Smart Billing Software

The set of solutions offered by the Business Operation Support System revolves around Smart Billing Software. Because billing is the nerve centre of the company, it oversees all the important data, including product catalogues, customers, rates, taxes, financial accounting, invoices, payments, debit and credit notes, dual ledgers, support for multiple currencies, and more. You can manage any business operation involving metered charges, recurring charges, event-based charges, and ad-hoc charges with the help of Smart Billing Software's engine, which offers unparalleled flexibility in setting up any kind of product, product packages, user-defined rating structures, tax rules, and more. With Smart Billing Software, any service model and offering can be easily integrated into a single platform. It is compatible with both pre-paid and post-paid payment systems. Due to its open API foundation, Smart Billing Software is highly compatible with other BOSS products, allowing for the construction of comprehensive solutions. Smart Billing is a pre-integrated component of Xsinfosol Solutions and is one of the BOSS solutions offered by Xsinfosol.

Pengaruh Kualitas Produk Dan Costumer Review Terhadap Keputusan Pembelian Di Lazada

This study aims to analyze the effect of product quality variables, customer reviews, and service quality on purchasing decisions at Lazada. With a case study studied on consumers who shop at the Lazada application in Srondol Kulon Village, Banyumanik District, Semarang City. The research method in this research is a quantitative approach. The population in this study were all buyers on the Lazada Application in Srondol Kulon Village, Banyumanik District, Semarang City, while the sample taken in this study was 100 Lazada Application users. Determination of the sample size using the method of non-proprability sampling technique and selection of respondents with purposive sampling technique. Data analysis in this study using the SmartPLS version 3 program. The data analysis technique used is the Structural Equation Modeling (SEM) equation model. From the results of the analysis and discussion of this study, it shows that the product quality variable has a significant influence on purchasing decisions, the customer review variable does not have a significant influence on purchasing decisions, and the service quality variable has a significant influence on purchasing decisions.

PENERAPAN ANALISIS SWOT DALAM MENENTUKAN STRATEGI PEMASARAN UMKM “MIE AYAM TOKET” DI JEMBER

ABSTRACT
 This study analyzes the application of SWOT Analysis (Strengths, Weaknesses, Opportunities, Threats) in increasing sales at "Mie Ayam Toket" MSMEs in Jember. SWOT analysis is an important tool in developing business strategies, which allows MSME owners to identify internal strengths and weaknesses, as well as external opportunities and threats that can affect business operations and growth. In the context of "Toket Chicken Noodles", this study evaluates how internal factors such as product quality and customer service, as well as external factors such as market demand and competition, can be optimized to increase sales. The study also includes other approaches such as B/C Ratio to strengthen effective marketing strategies. It is hoped that the results of the SWOT analysis can provide insight to MSME owners about how to overcome existing challenges and take advantage of possible opportunities to increase sales and business success. The conclusions of this study can be the basis for developing a more effective and innovative marketing strategy for "Mie Ayam Toket" in Jember.

Proposal of Industry 5.0-Enabled Sustainability of Product–Service Systems and Its Quantitative Multi-Criteria Decision-Making Method

In the wake of Industry 4.0, the ubiquitous internet of things provides big data to potentially quantify the environmental footprint of green products. Further, as the concept of Industry 5.0 emphasizes, the increasing mass customization production makes the product configurations full of individuation and diversification. Driven by these fundamental changes, the design for sustainability of a high-mix low-volume product–service system faces the increasingly deep coupling of technology-driven product solutions and value-driven human-centric goals. The multi-criteria decision making of sustainability issues is prone to fall into the complex, contradictory, fragmented, and opaque flood of information. To this end, this work presents a data-driven quantitative method for the sustainability assessment of product–service systems by integrating analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods to measure the sustainability of customized products and promote the Industry 5.0-enabled sustainable product–service system practice. This method translates the sustainability assessment into a multi-criteria decision-making problem, to find the solution that meets the most important criteria while minimizing trade-offs between conflicting criteria, such as individual preferences or needs and the life cycle sustainability of bespoke products. In the future, the presented method can extend to cover more concerns of Industry 5.0, such as digital-twin-driven recyclability and disassembly of customized products, and the overall sustainability and resilience of the supply chain.

New exact and heuristic algorithms for general production and delivery integration

This study considers a general production and delivery integration problem, commonly faced by a manufacturer that adopts make-to-order and commit-to-delivery business strategies. In the problem, the manufacturer determines acceptance or rejection of customers, produces products for accepted customers, and cooperates with third-party logistics providers who offer multiple shipping modes chosen by the manufacturer to deliver the finished products to customers. To better reflect the practical needs, this problem takes into account nonlinear production cost functions, nonlinear earliness and tardiness penalty functions, and nonlinear shipping cost functions of both shipping time and shipping quantity. The problem is to determine an integrated customer acceptance, production, and delivery plan by minimizing the total cost of production, shipping and inventory holding, and the total penalty of rejection, earliness, and tardiness. We investigate two variants of the problem where splittable delivery for the orders from customers is allowed and where splittable delivery is not allowed. For both the variants, we develop exact algorithms which achieve pseudo-polynomial running time in some practical situations, and design column generation-based heuristic algorithms to find near-optimal solutions efficiently. The computational results demonstrate that the heuristic algorithms are capable of generating near-optimal solutions for the instances generated randomly, with average optimality gap less than 4% in a reasonable running time.

Reinforcement Learning-Based Optimization for Sustainable and Lean Production within the Context of Industry 4.0

The manufacturing industry often faces challenges related to customer satisfaction, system degradation, product sustainability, inventory, and operation management. If not addressed, these challenges can be substantially harmful and costly for the sustainability of manufacturing plants. Paradigms, e.g., Industry 4.0 and smart manufacturing, provide effective and innovative solutions, aiming at managing manufacturing operations, and controlling the quality of completed goods offered to the customers. Aiming at that end, this paper endeavors to mitigate the described challenges in a multi-stage degrading manufacturing/remanufacturing system through the implementation of an intelligent machine learning-based decision-making mechanism. To carry out decision-making, reinforcement learning is coupled with lean green manufacturing. The scope of this implementation is the creation of a smart lean and sustainable production environment that has a minimal environmental impact. Considering the latter, this effort is made to reduce material consumption and extend the lifecycle of manufactured products using pull production, predictive maintenance, and circular economy strategies. To validate this, a well-defined experimental analysis meticulously investigates the behavior and performance of the proposed mechanism. Results obtained by this analysis support the presented reinforcement learning/ad hoc control mechanism’s capability and competence achieving both high system sustainability and enhanced material reuse.

Managing physical inventory and return policies for omnichannel retailing

As the retail industry increasingly adopts an omnichannel strategy amidst the growth of e-commerce, this study explores the interplay between inventory and return policies in such a setting. Specifically, we focus on “return losses,” defined as the losses incurred by retailers due to customer product returns. We target how these return losses impact retailers’ profits and physical inventories. While previous research has mainly concentrated on cross-channel returns, little attention has been paid to how omnichannel return policies affect store inventory and profit. We posit that profit-maximizing retailers allow consumers to select their purchase channels based on utility but require returns to follow specific policies. In this paper, we model four return policies based on the channel of return: original purchasing channel return, offline return, online return, and cross-channel return. We use a newsvendor model to construct an optimal profit function that accounts for the additional profit from offline return, uncertainty demand, and inventory cost. Our analysis identifies the conditions under which certain return policies are beneficial or detrimental to omnichannel retailers. We discover that the retailer's product pricing, return losses, and consumer return hassle costs are the main factors influencing the best return policy and inventory policy decisions. Moreover, whether to increase or decrease store inventory and the relationship between physical inventory and return loss depend on the return policy, price, and return hassle cost. Numerical simulations support our findings, which offer practical guidance for omnichannel retailers aiming to optimize their inventory and return policies.

PENERAPAN MODEL WATERFALL DALAM PERANCANGAN APLIKASI DIGITAL CUSTOMER RELATIONSHIP MANAGEMENT PRODUK FASHION

To win business competition and maintain market share, companies are required to be able to adapt to market conditions and use appropriate marketing strategies. Customer Relationship Management (CRM) is a marketing strategy to create and maintain good relationships with customers thereby reducing the possibility of customers moving to competitors. The aim of the research is to analyze and develop web-based CRM in the Marketing Information System at Toko Agung, East Jakarta. The research method used in this research is the Software Development Method using the waterfall model. The result is a web-based CRM system application that can manage customer data, product orders, payments and delivery of goods to customers. The implementation of this web-based digital CRM application is expected to make it easier for customers to select the desired product, place an order, make payments and receive goods without having to come to Toko Agung. For busy customers, this system is more efficient and effective. It is hoped that this convenience will have an impact on repeat purchases and will increase sales volume, which can then increase company profits. The Customer Relationship Management (CRM) application can simplify, speed up and optimize the quality of customer service, especially at Toko Agung, East Jakarta.

Eliminating Non-Value-Added Activities and Optimizing Manufacturing Processes Using Process Mining: A Stock of Challenges for Family SMEs

Family small and medium enterprises (FSMEs) differ from non-family SMEs regarding leadership type, human resource management practices, innovation orientation, change management, information and communication technology deployment, process maturity, and resource availability. These differences present challenges when leading any change. Process mining (PM) tools can optimize process value and eliminate non-added-value activities in FSMEs based on “Event Logs”. The present study investigates how a PM project is implemented in an FSME operating in the agri-food sector, focusing on challenges faced in every project phase to extract the most appropriate process that eliminates all sources of waste and bottleneck cases. Drawing upon the L*Lifecycle methodology combined with quality and lean management tools such as the fishbone diagram, Pareto diagram, and overall equipment efficiency (OEE), this study applied a PM project to a manufacturing process for an FSME operating in the agri-food sector. To achieve theoretical production capacity (TPC) and customer satisfaction, the method was analyzed and optimized using Disco and ProM toolkits. The results analysis using Disco and ProM toolkits gave clues about the organizational and technical causes behind the manufacturing process’s inefficiency. First, OEE showed that the studied FSME is struggling with equipment availability. Then, the implementation of the L*Lifecycle methodology allowed for the identification of five critical causes. An action plan to eliminate causes was proposed to the FSME managers.

Testing the effects of moral intensity news frames on consumer boycott intention

PurposeThis exploratory research examined how emphasizing a brand’s unethical behaviour through high moral intensity news framing influences consumer boycott intention.Design/methodology/approachThe hypotheses were tested and validated using two experimental studies that expose customers of real retail and personal care product brands to news articles that have high and low moral intensity news frames.FindingsThe results showed high moral intensity news framing’s positive effect on consumer boycott intention. The frame’s influence is moderated by moral awareness and partially mediated by perceived moral intensity and moral judgement. The findings suggest that consumers’ perception of the frame and their attitude towards the brand will have a substantial role in boycott intention.Practical implicationsThese research outcomes aid in the understanding of news framing effects on boycott intention, providing both insights for consumer activists and managerial implications for stewards of brands.Originality/valueWhile previous research have examined the impact of news frames on the typical audience, there has been relatively little focus on news framing’s impact on consumers and their decision to boycott brands. This study addresses this gap by applying the work on emphasis framing to a consumer decision-making context. It also introduces moral intensity framing to the news frame classification. In addition, this study expands current conceptualizations of individual ethical decision-making to help explain consumer boycott intent.

Implementasi Cyber Public Relations pada Instagram @dcikabakery

Researchers will examine whether Cyber Public Relations activities are effective in improving the D’cika Cakes & Bakery brand. The aim is to analyze the use of social media as an information medium for D'cika Cakes & Bakery in Cyber Public Relations activities referring to Chris Heuer's theory with four indicators, namely context, communication, collaboration and connection. This research was conducted using a qualitative approach with descriptive methods and using interviews and observation as data collection techniques. D'Cika uses various promotional media, including social media, television, digital platforms and billboards, to market its products or services. They specialize in business-to-business marketing communications and are directly involved in B2C activities. D'cika has two accounts, @dcikabakery.official and @dcikabakery, which are managed by the marketing communications team. The brand owner and marketing team have full control over the selection of promotional media. D'Cika Cakes & Bakery uses Instagram to maintain its reputation, utilizing various promotional media such as advertising, public relations and digital marketing. Brand owners and marketing teams control media selection, ensuring product quality and customer satisfaction.