No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
Knowledge Management and Business Processes in CEE Service Centers
Abstract
The objective of this research study is to examine the application and acceptance of knowledge management (KM) tools and methodologies in CEE BPO service centers. The research will employ a case study research design with embedded units to investigate how competitiveness is understood and reflected in management decision-making and operational practices within BPO centers. The study aims to provide insights to team members, particularly decision-makers and managers in the CEE region, by highlighting the current situation and future potential for sustainable competitive advantage. The study found that language skills, especially in the customer's mother tongue, are crucial for delivering high-quality service. Additionally, the research revealed that an attractive legal framework that supports personal leasing for center operations, along with taxation benefits for service centers in the EU zone, is common practice to control personnel costs and make the region appealing for service center establishment. Center managers face the challenge of balancing innovation creation activities with the pressure to deliver efficient services in terms of cost, resources, and quality.
ResearchGate has not been able to resolve any citations for this publication.
Businesses nowadays may save a significant amount of money by using technological solutions. It is impossible to deny this when considering the expenses of acquiring and training new personnel. When faced with such difficulties, technology is virtually always able to assist. Business Intelligence/Machine Learning (BI/ML) is an essential tool in today's decision-making process because of the many issues it has created for contemporary business decision-making. A comparative study of regression models, including linear regression, random forests, and gradient boosting, could unravel their effectiveness in predictive analytics within BI. Machine learning contribution in businesses is vital as it has a strong link with business intelligence, and it helps business decision-making in businesses. Without machine learning, business intelligence is not practical while making decisions, as business owners can't make decisions effectively. This paper will comprehensively review the noteworthy contributions of Machine Learning and its Impact on Business Intelligence. Further, it will discuss the challenges and opportunities of machine learning in business intelligence. Finally, the paper will discuss future correspondence about machine learning in businesses.
In today's digitally driven world, many small to medium Scale Enterprises (SMEs) find it difficult to manage or scale businesses due impediments in procuring and managing digital and software services. Many SMEs are unable to purchase the off-the-shelf software, as they are not tailor-made for their specific business use-cases and at times may not even fulfill the requirements. Creating custom software applications is an expensive undertaking and is difficult to maintain and scale. Further, the cost of deployment of these applications and ensuring availability either on premises or on cloud becomes a major hurdle. To overcome these hindrances, in this paper we propose the use of function-as-a-service technology in comparison to other options like micro-services and Service Oriented Architecture (SOA) and have highlighted the benefits in terms of ease of development and managing further we have put forth some economic benefits they have. FaaS can prove to be a major game changer service as it follows the model of pay-as-you-use and at idle time it can even scale to zero usage. This paper mainly discusses the option of using FaaS to help SMEs scale their application while cutting down on initial cost as well as economic impact in long run as compared to the other more traditional digital software service delivery models such as SaaS, ERP and custom application development.
This paper presents a solution for small businesses to gather statistics on the presence of their customers in and around their institutions, using Bluetooth technology. The solution includes a model of a mobile system based on Bluetooth technology that can provide information about the detectable devices’ relative position to create statistics on users’ presence in a specific timeframe. The research conducted shows that Bluetooth technology can be efficiently used to log the user’s relative position. This paper proposes a two-component system, which includes a mobile application and a cloud-based database with a simple online query interface. The prototype was implemented for the Android operating system and confirms the feasibility of the proposed solution. The developed prototype application was designed as a foundation for further commercial development. The proposed solution provides small businesses with an accessible way of collecting data on the presence of people without having to buy specialized equipment.
An approach to use Operational Intelligence with mathematical modeling and Machine Learning to solve industrial technology projects problems are very crucial for today's IT (information technology) processes and operations, taking into account the exponential growth of information and the growing trend of Big Data-based projects. Monitoring and managing high-load data projects require new approaches to infrastructure, risk management, and data-driven decision support. Key difficulties that might arise when performing IT Operations are high error rates, unplanned downtimes, poor infrastructure KPIs and metrics. The methods used in the study include machine learning models, data preprocessing, missing data imputation, SRE (site reliability engineering) indicators computation, quantitative research, and a qualitative study of data project demands. A requirements analysis for the implementation of an Operational Intelligence solution with Machine learning capabilities has been conducted and represented in the study. A model based on machine learning algorithms for transaction status code and output predictions, in order to execute system load testing, risks identification and, to avoid downtimes, is developed. Metrics and indicators for determining infrastructure load are given in the paper to obtain Operational intelligence and Site reliability insights. It turned out that data mining among the set of Operational Big Data simplifies the task of getting an understanding of what is happening with requests within the data acquisition pipeline and helps identify errors before a user faces them. Transaction tracing in a distributed environment has been enhanced using machine learning and mathematical modelling. Additionally, a step-by-step algorithm for applying the application monitoring solution in a data-based project, especially when it is dealing with Big Data is described and proposed within the study.
This article considers the concept of information support of web community member personal data verification system. It has been established that information support of verification system depends on the following parameters: profile filling level, profile data and content actuality level, administrative authority, web user activity level and level of compliance with virtual community rules. The paper also analyzes an actual task of developing methods for determining information support of web community member personal data verification system. The level of information support of web community member personal data verification system allows evaluating the effectiveness of verification system in web-community management. It is concluded that the higher is the level of information support of web community member data verification system, the better is the community management performance, and therefore, web community operation.
Service economy, service science, service-dominant logic and servitization are apparently related terms, but hard to distinguish on the first sight. All of them emerged and are located in different economic disciplines, which do not ease things at all. Accordingly, this paper provides on the one side a fundamental theoretical background on these topics and on the other side facilitates subsequent research by providing some reference points.
On the begin, the topic of service economy and its increasing share on total employment are elaborated to show its current importance. Consequently, the notion and definition of the term service is conducted, which is followed by the discussion about goods, their differences to service and the drivers for the transition to a dominant service economy. Furthermore, the concept of business models and its varying characteristics are reviewed, since they play a major role in the service economy. And, the last section leads finally over to the intrinsic topic such as research approaches on the Services.
Once service organisations recognise collaborative e-marketplace as a strategic business approach, they can embrace the ultimate form of competition enabled by the internet. Hence, the collaboration makes it possible to create customer-driven value-chains by harmonising demand and supply channels. Then service organisations can reduce the costs, speed up time-to-market, and achieve flexibility by making decisions based on who can deliver the required services at the right price, quality and place. Thus, we study in this paper the influences on the development of collaborative e-business in the service organisations. We start with a consideration of the current state and the relations between e-business and c-business. We continue with a discussion of features, chances and challenges of the collaborative business in contemporary vibrant and fast rising markets, the businesses are acting in. We examine also a successful collaboration planning issues, as well as different aspects affecting the enlargement of collaborating businesses. And, we conclude with a viewpoint on future collaboration trends in the service organisations.
Purpose
While nowadays an extensive literature promoting knowledge management (KM) exists, there is a worrying shortage of empirical studies demonstrating an actual connection between KM activities and organizational outcomes. To bridge this gap, this paper aims to examine the link between KM practices, firm competitiveness and economic performance.
Design/methodology/approach
This paper proposes a framework of KM practices consisting of human resource management (HRM) and information communication technology (ICT). These both are hypothesized to impact competitiveness and economic performance of the firm. Hypotheses are then tested with structural equation modeling by using a survey dataset of 234 companies.
Findings
The results show that HRM and ICT practices for managing knowledge are quite strongly correlated and have a statistically significant influence on both financial performance and competitiveness of the firm. The findings also indicate that ICT practices improve financial performance only when they are coupled with HRM practices.
Research limitations/implications
The data are limited to companies from Finland, Russia and China.
Practical implications
The paper contributes to managerial practice by pointing out the importance of utilizing a combination of both social and technical means for KM and illustrating that they do matter for the company bottom line.
Originality/value
This paper contributes to the literature on knowledge‐based organizing by empirically analyzing the performance impact of various areas of KM. It thereby tests the proposition put forth in many previous theoretical and case‐based studies that KM promotes high organizational performance. It also addresses the interaction of social and technical KM practices in producing organizational outcomes.
This research examines media richness by modeling face-to-face, telephone, and electronic media as one construct and testing its performance implications. The context is the third-party logistics industry, in which a customer firm allows a service provider to assume responsibility for all or part of a critical business process. This business-to-business service environment is characterized by high levels of complexity (uncertainty, variability, equivocality) and network interdependence, key contextual attributes that enhance media richness' impact. We found a direct effect of media richness on relational performance and through it, indirect effects on satisfaction and loyalty. Furthermore, we found a direct effect of media richness on loyalty, which suggests that service firms in networked relationships provide loyalty-inducing benefits the genesis of which is not in the satisfaction created by the service itself. While past studies have examined the relationship of richness-related constructs and performance, no significant link was found. Our study is the first to demonstrate that media richness can affect firm performance when businesses interact in a complex environment.
In this paper we develop a knowledge-based view on the choice of knowledge transfer mechanisms in franchising that integrates
results from the information richness theory. Starting from the information richness theory we argue that tacitness of system
knowledge, operationalized by codifiability, teachability and complexity, determines the information richness of the knowledge
transfer mechanisms of franchising firms. We examine the following hypotheses: (1) If the franchisor’s knowledge is characterized
by a high degree of codifiability and teachability and a low degree of complexity, knowledge transfer mechanisms with a lower
degree of information richness are used; (2) If the franchisor’s knowledge is characterized by a high degree of complexity
and a low degree of codifiability and teachability, knowledge transfer mechanisms with a higher degree of information richness
are used. We test these hypotheses by using data from 52 franchising firms in the Austrian franchise sector. The data provide
support for the hypotheses.
KeywordsKnowledge transfer–Information richness–Knowledge-based view of the firm–Tacitness of knowledge–Franchising
Diese systematische Einführung bietet einen Einstieg in die Planung und Durchführung von qualitativen Interviews zur Analyse sozialer Systeme (Gemeinden, Organisationen, Gruppen oder Familien). Die Autoren zeigen verschiedene Möglichkeiten zur Erstellung von Forschungsdesigns und führen drei sich ergänzende Interpretationsverfahren vor. Darüber hinaus erläutern sie Strategien der Qualitätssicherung und informieren über den methodologischen Hintergrund dieses interpretativen sozialwissenschaftlichen Verfahrens. Das Buch wendet sich an Studierende der Soziologie, Politikwissenschaft, Pädagogik, Psychologie oder Wirtschaftswissenschaften sowie Personen, die sich beruflich mit Organisationsdiagnosen oder prozeßorientierter Unternehmensberatung beschäftigen.
The growing number of sales channels through which customers can make purchases has made it imperative for managers to understand how customers decide which channels to use. However, this presents a significant challenge because there is reason to believe the channel decision process evolves over the lifetime of the customer. The authors document the existence and nature of this phenomenon by analyzing the evolution of a customer's channel choice decision process from a trial stage to a posttrial stage. First, they analyze data for a book retailer and replicate their analysis using data from a durables and apparel retailer. Their results suggest that (1) customers' decision processes do evolve, (2) a minority but sizeable segment changes decision processes within the observation period, and (3) customers who change do so from a decision process in which they are highly responsive to marketing to one in which they are less responsive. The authors illustrate and discuss the implications for both managers and researchers.
Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are heterogeneously distributed across firms and that these differences are stable over time, this article examines the link between firm resources and sustained competitive advantage. Four empirical indicators of the potential of firm resources to generate sustained competitive advantage-value, rareness, imitability, and substitutability are discussed. The model is applied by analyzing the potential of several firm resources for generating sustained competitive advantages. The article concludes by examining implications of this firm resource model of sustained competitive advantage for other business disciplines.
Is concerned with human value management, examines the relationships between organizations' competitiveness, innovation advancements, and knowledge management and presents a set of considerations regarding how these relationships affect strategic management and the formulation of competitive strategies. By considering how knowledge development is related with personal characteristics and personal development, this article attempts to provide useful insights on the linkages between innovation and competitiveness. These considerations point out the importance of knowledge development and the role of knowledge management in order to assure competitiveness. This work proposes also a conceptual model, with special focus on the relationships between knowledge management, competitiveness, and innovation. The major factors are presented and directions for future research are suggested according to the proposed model.
This study intends to capture in essence the challenges and the opportunities that might arise while implementing a Knowledge Management (KM) system in an outsourcing environment. The objective of this study is to emphasize the significance of KM in an outsourcing environment, thereby trying to reduce manpower turnover and knowledge loss, thus saving time, funds and effort while training and setting up similar processes, or ramping up an existing process or project. The significance of KM is upheld in the fact that most organizations, including the Business Process Outsourcing (BPO) sector, has come to realize the importance of KM adoption and implementation. However, most of these face a challenge in collating and assimilating all information and experiences, which, if done, would create a ‘knowledge pool’. Even if knowledge is captured, getting people to contribute and utilize stored knowledge assets is a challenge. They are not cognizant of the benefits of such an exercise that ‘people can empower people’ by means of a robust KM system, which in turn would lead to the development of service intensity, improved quality, standardization of processes and globalization, further leading to a better understanding of the organizational goals by employees, effective learning processes, improved responsiveness, employee retention, minimized costs, knowledge asset creation, initiatives, innovation and above all, operational excellence which benefits the organization as a whole. The study is the first of its kind and investigates the awareness levels of KM in outsourcing environment and the scope of effective implementation of a KM strategy in the workplace of these organizations. Primary data was collected by means of a comprehensive questionnaire and analyzed.
Argues that the knowledge management process can be categorized into knowledge creation, knowledge validation, knowledge presentation, knowledge distribution, and knowledge application activities. To capitalize on knowledge, an organization must be swift in balancing its knowledge management activities. In general, such a balancing act requires changes in organizational culture, technologies, and techniques. A number of organizations believe that by focusing exclusively on people, technologies, or techniques, they can manage knowledge. However, that exclusive focus on people, technologies, or techniques does not enable a firm to sustain its competitive advantages. It is, rather, the interaction between technology, techniques, and people that allow an organization to manage its knowledge effectively. By creating a nurturing and “learning-by-doing” kind of environment, an organization can sustain its competitive advantages.
This research examines the linkages between human resource management and knowledge management. Specifically, the association between four areas of human resource management (training, decision-making, performance appraisal, and compensation and reward) with the five areas of knowledge management (knowledge acquisition, knowledge documentation, knowledge transfer, knowledge creation, knowledge application) is explored. The statistical results suggest that a knowledge organisation requires a different management approach than the non-knowledge organisation. Hence, the role of human resource management is also unique. In terms of employee development, the focus should be placed on achieving quality, creativity, leadership, and problem solving skill. The design of a compensation and reward system should be on promoting group performance, knowledge sharing, and innovative thinking. The performance appraisal must be the base of evaluation of employee’s knowledge management practices, and an input for directing knowledge management efforts.
This background chapter defines knowledge management, its components, processes, and outcomes. It addresses the importance of knowledge management for higher education, in general, and for institutional research, in particular.
Even though intrafirm transfers of knowledge are often laborious, time consuming, and difficult, current conceptions treat them as essentially costless and instantaneous. When acknowledged, difficulty is an anomaly in the way transfers are modeled rather than a characteristic feature of the transfer itself. One first step toward incorporating difficulty in the analysis of knowledge transfer is to recognize that a transfer is not an act, as typically modeled, but a process. This article offers a process model of knowledge transfer. The model identifies stages of transfer and factors that are expected to correlate with difficulty at different stages of the transfer. The general expectation is that factors that affect the opportunity to transfer are more likely to predict difficulty during the initiation phase, whereas factors that affect the execution of the transfer are more likely to predict difficulty during subsequent implementation phases. Measures of stickiness are developed for each stage of the transfer to explore the predictive power of different factors at different stages of the process. A cross-sectional analysis of primary data collected through a two-step survey of 122 transfers of organizational practices within eight firms illustrates the applicability of the model and suggests several issues for further research.
Because of the huge scale and numerous components, a massive database system’s availability has become a serious challenge. Many database replication technologies are used to increase the MTTF, but few are provided to decrease MTTR in massive database systems where the traditional backup methods are not feasible for expensive human cost. Based on analyzing the characteristics of the data in massive databases, we propose a novel approach called Detaching Read-Only (DRO) mechanism and its variation DRO+. It decreases MTTR through reducing the size of physically changing data in every database by detaching data on node granularity. The analysis and experiment results show that our approach can not only reduce MTTR by an order of magnitude, but also reduce the expensive human cost without extra hardware cost.
Case Study Research: Design and Methods
- R K Yin
Episodic interviewing. Qualitative Researching with Text, Image and Sound
- U Flick