Changing Customer Requirements Research Articles

Качество обслуживания потребителей как критерий повышения конкурентоспособности транспортных компаний при доставке грузов

Modern conditions in the service market orient the country's transport companies to the availability and quality of transport and logistics services in the field of freight traffic, the conditions for creating their quality while reducing the level of transport costs. Many companies appear in the road transport industry offering a different set of services related to the delivery of goods, such as information, commercial, technological, service, etc. However, despite the presence of a significant number of such companies in the transport services market, most of the customers are not satisfied with the quality of their provision, since along with the growth of competition, the requirements imposed by consumers on the quality of such services also increase. To meet these requirements, it is necessary to study the needs of consumers, determine the capabilities of competitors, establish and implement a marketing strategy. In order for the consumer to be guided in the market of motor transport services in the work on choosing an algorithm for choosing a transport company, which was based on ranking the identified indicators of the quality of transport services, measuring them for consumers and calculating the rating of transport companies, evaluating the delivery of goods. This technique helps the consumer to make a choice, giving preference to a company with the highest integral rating of transport services, therefore, the highest level of quality of services provided. To increase the number of customers and increase revenues, transport companies need to improve the quality of transport services through an individual approach to each client and his requests. The competitive advantage will be the one that can respond flexibly to changing customer requirements for transportation services and at the same time provide better quality services.

Влияние структуры управления на инновационные возможности организации

The current economic situation, characterized by rapidly changing market rules, requires business structures to respond immediately in order to maintain competitive advantages. The frequently changing requirements of customers, whose priorities are updated as quickly as technological breakthroughs and innovations dictate their consumer conditions to the business. In addition, newly created companies structure their activities in a unique way in accordance with changing customer requirements and challenge traditional corporate structures. The article considers the issues of functioning, development and improvement of organizational management structures of organizations in the implementation of innovations. The features of hierarchical and organic types of management are highlighted. The elements of the organizational structure of the enterprise inherent in any management model are presented. The results of a survey of 148 large Russian enterprises conducted by KPMG consulting company together with the Agency for Strategic Initiatives (ASI) are considered. The author's conclusions based on the results of the study are made. Recommendations for the successful functioning of the organization in the implementation of innovations are proposed.

THE IMPORTANCE OF APPLYING SELECTED INDUSTRIAL ENGINEERING TOOLS AND METHODS IN PROCESS IMPROVEMENT

Among the key activities of managing an organisation is to be able to make timely and correct decisions. Making the right decision is necessary to ensure the organisation's competitiveness [Lestyanszka 2014a]. Organisations are trying to reduce production costs as much as possible, but this, on the other hand, brings negatives in the form of products that do not meet customer expectations. This phenomenon, however, has other downstream processes that burden the organisation and make it more difficult to continue its activities. These are customer complaints, the cost of eliminating the claimed defects, downtime, etc. [Lestyanszka 2014b, Husain 2021]. Therefore, the successful functioning of any organisation depends on its ability to adapt to changing customer requirements, as these are a priority in the market [Szander 2014, McDonnell 2013]. An effective tool for quality improvement is statistical methods and tools, which are not only advisable but essential to be implemented in production processes. Without systematic quality management, an organisation cannot grow, as it has to combine enormous efforts in developing and introducing new products with maximum quality maintenance of the already established ones.

Modelling the dynamics of customer requirements considering their lability and sensitivity in product development

Enterprises are challenged with fulfilling continuously changing customer requirements (CRs) that are influenced by many uncertain factors. Existing research only modelled the dynamics of CRs (DoCRs) by focusing on the potential resultant effects of CR changes, while lacking insightful exploration of the change characteristics of CRs themselves. To fill this gap, an online review-based DoCRs modelling method is proposed considering the lability and sensitivity of CRs by analyzing the changes in customers’ perceptions of product features over time. First, CRs in online reviews are extracted through Latent Dirichlet Allocation. Second, Bidirectional Long Short-Term Memory is applied to measure customer sentiments in different periods towards specific product features. The probabilistic linguistic term sets are employed to characterize customer sentiment distributions which are then incorporated into the modelling of DoCRs. Third, a novel CRs classification cube is established by integrating the lability, sensitivity, and importance of CRs from an evolution-adapted perspective. Finally, the DoCRs of a smartphone is investigated as a case study to demonstrate and effectiveness of the proposed methodology. Several managerial implications for the selection and adjustment of product development strategy are provided.

Enhancing decision-making of IT demand management with process mining

PurposeDigitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.Design/methodology/approachIn this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.FindingsThe study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.Originality/valueThe implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

Enhancing US Software Companies' Competitive Edge with Agile Project Management

The primary purpose of this study was to examine how the adoption of Agile Project Management practices can help US-based software companies gain a competitive advantage in the rapidly evolving global marketplace. With ever-increasing customer demands and changing technology landscapes, it was crucial to assess whether agile methodologies could effectively address these challenges. The software industry in the USA faced challenges related to project delays, cost overruns, and difficulties in responding to changing customer requirements. Traditional project management approaches often proved inadequate in such dynamic environments. The study aimed to determine whether Agile Project Management could mitigate these issues and improve competitiveness. The research employed a mixed-methods approach. Quantitative data were collected through surveys distributed to software companies implementing agile practices. Qualitative insights were gathered through in-depth interviews with industry experts. Data analysis involved statistical techniques for quantitative data and thematic analysis for qualitative data. The findings revealed that Agile Project Management significantly improved software development processes. Agile adoption also fostered better collaboration among cross-functional teams. Moreover, Agile practices positively impacted software quality and customer satisfaction, ultimately contributing to a competitive edge. Based on the research findings, it can be concluded that Agile Project Management has a substantial positive impact on the competitiveness of US-based software companies. To enhance competitiveness, it is recommended that US software companies consider the adoption of Agile Project Management practices. Additionally, organizations should invest in training and cultural changes to facilitate a smooth transition to agile methodologies. Continuous improvement and alignment with agile principles are essential for sustained competitiveness. Keywords. Agile Project Management, Software Development, Competitiveness, Customer-Centric, US Software Companies

Multicriteria Decision-Making Framework for Supplier Selection: A Customer Community-Driven Approach

Supplier selection is the core of enterprise supply chain management. It involves a systematic evaluation of potential supply partners. Customer expectations for products and services are rarely considered when selecting suppliers. Considering customer factors in supplier selection faces many problems, including customer segmentation, importance ranking for customer requirements, and answering how customer requirements guide the supplier selection. For the above, a multicriteria supplier selection framework driven by customer communities is proposed. It includes three stages. In the first stage, a customer segmentation method is used to discover customer communities. In the second stage, the weighted interval rough number method quantitatively analyzes the customer requirements in each community, and then expert knowledge is integrated to determine the importance of supplier selection indicators. In the third stage, a genetic algorithm based on a stochastic tournament model is used to search for the optimal suppliers. A practical case study of a household refrigerator was conducted to illustrate the performance of our framework. A simulation experiment was designed to verify that our framework could update the supplier selection scheme according to changes in customer requirements in a dynamic scenario.

Digital Transformation in Back-Offices of German Insurance Companies

Digital transformation affects the back offices of incumbent insurance companies. Digital innovations are implemented to be able to offer customers new products and services. We conduct multiple case studies with four German insurance companies. We analyze the impact of digital transformations on company-internal stakeholders with the Technology-Organization-Environment (TOE) framework. We derive 12 influencing factors and corresponding practical implications. Back-office systems are updated using standard software, if available. The goal is to stay flexible for future developments, too. State-of-the-art technologies are tested and only carefully implemented. Necessary reorganizations have significant impacts and are accomplished best with a trusting company culture, good internal communication, and well-trained employees. Efficiency gains from automating routine functions can and are intended to counter labor shortages. After the implementations, skilled employees must handle more specialized and demanding tasks, which cannot be automated easily. Impulses for digital transformation mainly result from continuously changing customer requirements and respective competitive pressure, while regulatory requirements often complicate implementations.

Explaining sustainability performance and maturity in SMEs – Learnings from a 100-participant sustainability innovation project

Small and medium enterprises (SMEs) are the backbone of many economies and shape the sustainability of both production and consumption. SMEs differ drastically in their sustainability performance and maturity. The objective of this paper is to assess what aspects of SMEs' activities, including their links to stakeholders in their supply chains, explain a company's sustainability performance. Using a literature-based theoretical framework for assessing SME sustainability performance and maturity, the study conducts a survey with participants in a 100-company sustainability innovation project conducted in the Greater Copenhagen region. The sample of companies reaches across several industries including construction, hotel/conference, information technology, and manufacturing. The study analyses survey data using paired sample t-tests and regression analyses. The results show that the following factors help explain the sustainability performance and maturity of SMEs in the sample: the degree of customer involvement in product and process development; engaging, communicating and partnering with customers; customer segmentation, technology and innovation as constituent parts in the business strategy; and the amount of time dedicated specifically to commercial and marketing efforts and process development. The study shows that devoting time and resources to engage with customers in product and process development will lead to increased sustainability performance and maturity. These results contrast with the traditional norm that companies develop as a reaction to changing customer requirements. The novelty of this study lies in bringing to light the aspects within the management of SMEs contribute to explaining their sustainability performance, and thus can be used to guide improvements. Unveiling this allows SMEs to deploy sustainability-focused action.

Assessment of product resilience towards the changing customer requirements

Changes of customer requirements (CRs) are inevitable disturbances for products which will lead to product obsolescence or frequent redesign. The property of product defending and recovering from the shock of ever-changing CRs is resilience. It is beneficial for designers to explore and evaluate product resilience towards changing CRs. Fortunately, various resilience assessment methods in engineering realm have offered some significant insights. Motivated by the deficiencies of the existing studies and the advantages of engineering resilience assessment methods, product resilience towards changing CRs is measured. Firstly, joint customer satisfaction is defined by integrating competition analysis and importance analysis. Secondly, the evolution trends of CRs are depicted and captured based on a modified grey model and polynomial fitting, respectively. Then, a three-stage model considering absorption, adaptation, and recovery is established to evaluate product resilience. Lastly, a case study of an electric vehicle is implemented to elucidate the utility and effectiveness of the proposed method.

Impact of Covid-19 on Irish airport stakeholder relationships

COVID-19 related travel restrictions led to a significant contraction of aviation activities, necessitating significant State support for the sector. This paper assesses the impact of the pandemic and Irish airport stakeholder relationships, exploring a widely expressed view that effective aviation collaboration is essential to recovery from COVID-19. Interviewees reported significant positive stakeholder interaction during the shutdown period, with airports supporting rapidly changing customer requirements, operationally and business-wise. However, each stakeholder organisation then focused on its own distinct challenges. Airport Stakeholder engagement during this COVID-19 period concentrated on short-term planning and objectives. Implications for airport managers are identified. This research makes a theoretical contribution regarding the impact on airports and stakeholders when sudden adverse developments affect the industry.

Complex product configuration updating oriented by changing customer requirements

Changes of customer requirements inevitably occur in the process of product design and manufacturing, which results in substantial costs in product development. Enterprises have to update product configuration schemes to meet new customer requirements and maintain competitiveness. Recent studies have attempted to solve this problem with the ‘two-stage’ model (optimisation of change propagation and update scheme). They have largely ignored the correlation between the two stages, which leads to extra costs in practice. Therefore, this paper proposes a master-slave coordinated optimisation model, in which the design of update scheme was the leader and the optimisation of change propagation path was the follower. The upper optimisation model was constructed to obtain a change propagation path with the minimum propagation range. And the lower optimisation model was constructed to obtain a product configuration update scheme with the highest satisfaction. Meanwhile, the diversity of the optimal update scheme from the lower model was fed back to the upper model, and the change propagation probability was adjusted. This causes further changes in the process of change propagation. Finally, cases of sanitation vehicles and motorbike engines were taken to verify the effectiveness of the proposed model.

AI impacts on supply chain performance : a manufacturing use case study

The integration of cross-company activities to form global supply chains (SC) has several benefits, including reducing costs, minimizing energy and resource waste, and promoting relationships for improving all network actors. However, as the number of tiers of suppliers and customers increases, monitoring processes and identifying problems becomes more challenging, which can threaten the continuity of the SC. To address this issue, the EU knowlEdge project proposes using artificial intelligence (AI) solutions that are distributed, scalable, and collaborative to enable automatic monitoring and learning in the SC. This approach replaces rigid organization with flexible networks that leverage self-learning algorithms and automatic value creation, thereby facilitating knowledge sharing. The project unifies technologies from various domains, including AI, data analytics, edge, and cloud computing, into a software architecture that offers a systemic solution rather than an incremental improvement. This architecture enhances SC performance, including adaptability and autonomy, and enables industry to adopt adaptive strategies. The platform’s functionality is tested in manufacturing, where it will improve production monitoring and planning and enable human intervention and learning. The AI application is expected to increase performance on various business and production indicators, which will also have an impact beyond the factory floor. With this approach, managers can respond quickly to changing customer requirements, while deviations in planned processes can be addressed more effectively. Additionally, the research conducted by the project will provide insights into future management and learning in SC.

Method of Fuzzy Analysis of Qualitative-Environmental Threat in Improving Products and Processes (Fuzzy QE-FMEA)

Improving products and production processes is necessary to ensure the competitiveness of the organisation. As part of these improvements, the popular approach is to use the FMEA method (Failure Mode and Effect Analysis). In the traditional FMEA approach, only the qualitative aspect is included, i.e., the analysis of the quality level of products or processes, its possible incompatibilities, and then proposing improving actions for them. It seems insufficient in times of expansion of the idea of sustainable development and dynamically changing customer requirements. Hence, the purpose of the research is to develop a fuzzy QE-FMEA method to simultaneously analyze hazards for product quality and the natural environment. This method will be based on a fuzzy decision environment. The main elements of originality of the developed method are: (i) extension of the characteristics of the selection of ratings for indicators with triangular fuzzy numbers and the development of a new characteristics of the selection of ratings for the environmental impact indicator, (ii) development of a selection matrix for the qualitative-environmental indicator (QE) according to the rules of triangular fuzzy numbers, (iii) determination of the method of estimating the value of the threat priority, additionally considering the qualitative-environmental indicator (RQE). The complement of research is developed procedure of the Fuzzy QE-FMEA method. It was shown that it is possible to include the effects of incompatibilities (effects of defects occurring in products or processes), which were simultaneously assessed considering the importance and impact on the natural environment. This method will be useful for any company for analysing defects of any products or processes mainly with significant impact on the natural environment.

Evolutionary Algorithm for Software Project Scheduling Considering Team Relationships

During software development, human relationships between team members have a significiant influence on development efficiency. Meanwhile, finishing tasks might require new skills that employees have not yet grasped due to changes of customer requirements or other reasons. However, such factors have not been taken seriously in existing software project scheduling work. To address this, a software project scheduling model considering the team relationships is established, which minimizes the duration and cost of software projects by finding the best employee-task allocation. The model introduces the communication cost factor of each team member, and its quantitative connections with changes in human relationships and the growth of skill proficiency are analyzed, respectively. In addition, a selection mechanism for external employees is designed to meet new skill requirements. To solve the model, a bi-population discrete evolutionary algorithm based on information feedback is proposed. Some initial individuals are generated by utilizing heuristic information of "employee suitability". Adaptive tuning of the subpopulation size is realized by the feedback of "evolutionary quality". The selection probabilities of different crossover operators are adjusted according to the "improvement rate". Additionally, a local search strategy is developed based on the "degree of team cooperation" and the ‘improvement rate’. The experimental results show that by considering human relationships under different communication cost factors, the scheduling performance is significantly improved. Compared with the state-of-the-art algorithms, the proposed algorithm can obtain a schedule with a higher quality in problems of different scales.

A new Instrument for Production Control: The Smart Order Concept

Production control is an essential component of a production system used to monitor and manage production orders. Centrally controlled production systems rely on basic data management, such as storing the bill of materials and required work schedules. Components of customer orders are added to generate the corresponding production orders. However, this type of production control can pose serious problems in case of unforeseen events such as machine failure or changing customer requirements during production. In such scenarios, costly and time-consuming re-scheduling becomes necessary, which endangers the company's competitive position and leads to data retention issues. This paper introduces a new method of production control based on the concept of smart orders. Smart orders use smart contracts for autonomous routing based on programmed information in the source code, enabling self-control through the production system. Smart contracts are transaction programs that work with ‘if-then logic”, allowing for partially flexible process schedules and reducing the need for human intervention. The smart order uses the functionalities of blockchain technology, such as security, transparency, and immutability, to ensure the integrity of production data. The paper concludes by presenting the expected value propositions of smart order-based production control on the production system. Depending on the production control system used, companies can integrate the results presented in this paper into their own blockchain implementation strategy.

Influence of Agility on the Innovation Capability of Organizations – A Systematic Review of Influencing Factors

The increasing dynamization of markets, changing customer requirements and unpredictable occurrences pose new challenges for product development and design. Agile methods and processes can serve as a solution to secure the innovation capability of organizations in this environment. Since the areas of agility and innovation capability of organizations have mostly been treated separately in research, this research effort is focusing at hollistically collecting success factors for agility and success factors for the innovation capability of organizations and analyzing them in detail - including collecting indicators and directional characteristics. The analyzed factors are specifically focused on the development of mechatronic products and are intended to serve as a type of library that enables organizations and researchers to understand their own situation as best as possible, select appropriate recommendations for action in a targeted manner, and track their implementation / operationalization on the basis of the corresponding indicators and characteristics. This research work thus makes a contribution to sustainably increasing innovation capability and agility of industrial organizations.

Optimization of customer satisfaction using fuzzy analytic hierarchy process method

Today's competitive environment is characterized by accelerated product renewal, the rapid development of production, information and communication technologies, the computerization of many aspects of economic activity, and changing customer requirements. In such a competitive context, the customer has become the key factor in the manufacturing process, requiring products designed to fully meet his expectations at competitive prices. The question of customer satisfaction, and therefore the quality of the product, has become a major concern for companies. In this context, the purpose of this study is to help a company specialized in producing vehicles, and that aims to launch a new vehicle model, classifying and prioritizing the customers’ requirements, and thus determining which of the 6 available models meets the customers’ expectations the most, using a fuzzy AHP approach. This study was based on 5 Customer Requirements (CR) that represent the main characteristics of a vehicle : Price (CR1), Fuel Consumption (CR2), Security (CR3), Comfort (CR4), and Design (CR5). A sample of 5 customers was considered for this study. The results showed that price (CR1) and security (CR3) had the highest priorities among the customers’ requirements. Based on these results, we were able to classify the 6 vehicle models and determine which of these models meet the customers’ requirements the most, using the Analytic Hierarchy Process method (AHP).

Dynamic Resource Allocation Using an Adaptive Multi-Objective Teaching-Learning Based Optimization Algorithm in Cloud

Resource allocation is a non-polynomial complete problem in the cloud data center that selects the proper resources to execute many fine computational granularity tasks. Customer requirements and capacity of applications change frequently. To bridge the gap between frequently changing customer requirement and available infrastructure for the services, we propose a dynamic resource allocation strategy using an adaptive multi-objective teaching-learning based optimization (AMO-TLBO) algorithm in Cloud computing. To improve the exploration and exploitation capacities, AMO-TLBO introduces the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. Moreover, a grid-based approach to adaptively assess the non-dominated solutions maintained in an external archive is used. The objectives of AMO-TLBO include minimizing makespan, cost and maximizing utilization using well-balanced load across virtual machines. The evaluation results show that the proposed algorithm outperforms TLBO, MOPSO and NSGA-II algorithms in terms of different performance metrics.

Realisation of Design Methodologies and Tools in Modern Manufacturing Systems

Engineering design is the basis for technological advancement and the development of new products. Many changes have emerged over the last few decades due to scientific advancements, evolution in novel engineering materials, advances in computational technology, the opening up of the global village, economic constraints, short life spans of products, and the need for a responsive life cycle design paradigm in engineering products. To meet customer or operational requirements, a certain design methodology is used to design and develop products. This has resulted in notable growth in product design methodologies across disciplines, particularly architecture, engineering, and industrial designs. The engineering design methodology has addressed design procedures, epistemological issues, and working procedures in the design disciplines for several decades. In this article, the research seeks to delve into novel design methodologies currently in use and interrogate their limitations and advantages to create synergies among the best practices in engineering design approaches, with particular emphasis on responsiveness to continuously changing customer requirements. To achieve this, special emphasis will be placed on a design methodology for life cycle, end-of-life, concurrent engineering, eco-design, and reconfigurable design. Based on a strategic focus, the drive is for innovative engineering design that requires design approaches that respond to continuous product changes. The results from this study demonstrate the relationships between engineering design methodologies and solution models that respond to industry and customer requirements.