Real-life Business Research Articles

Using business games in administration teaching: A case study of the entrepreneurial Matrix Game

Business games, also known as business simulation games, are educational tools used in teaching business administration that simulate real-life business scenarios. They provide a controlled environment for students to practice decision-making, problem-solving, and critical thinking skills in a risk-free environment. In this article we applied the Entrepreneurial Matrix Company Game to a sample group of undergraduate business students. This game is a learning methodology that simulates the step-by-step creation of a new business model in a controlled environment. It is an interactive tool that allows participants to experience different situations and challenges that may arise when opening a new business. Our objective was to identify the importance of such a tool for entrepreneurial motivation, and at the end of this research we identified that the company game Matriz Empreendedora can help identify potential obstacles and opportunities, allowing student-entrepreneurs to better prepare themselves to launch a new business.

Breaking barriers and empowering marginal women entrepreneurs in Bangladesh for sustainable economic growth: a narrative inquiry

PurposeThe bread and butter of marginal communities primarily rely on their artisanal work, to which the communities’ women have notable contributions despite facing numerous challenges. This study aims to unveil the challenges along with latent opportunities of different marginal women entrepreneurs in the rural areas of Bangladesh.Design/methodology/approachThis study used narrative inquiry to explore the real-life business phenomena of 15 marginal women entrepreneurs with more than 5 years of business experience living in 4 districts of Bangladesh. This approach was used to document participants’ responses through the storytelling of their daily business experiences.FindingsThe findings of this paper indicate that vulnerable living conditions, social negligence, availability of substitutes, frequent sickness, increasing price of raw materials, lack of entrepreneurial skills and lack of managerial skills are the major challenges of marginal women entrepreneurs. In contrast, minimum capital requirement, home-based business, traditional profession, retaining cultural heritage and lack of accountability are the main opportunities that motivate marginal women to continue their entrepreneurial activities.Research limitations/implicationsThe insight of this research can promote and sustain marginal women entrepreneurship and aid researchers, policymakers and businesses in improving the various entrepreneurial aspects of informal community entrepreneurs in developing countries. However, the study was limited to five marginal community entrepreneurs (Rishi, Kumor, Jele, Cobbler and Kamar) in Bangladesh. Therefore, conducting future research encompassing all marginalized communities is recommended, and empirical studies on this domain are highly encouraged.Social implicationsThe insight of this research can promote and sustain marginal women entrepreneurship and aid researchers, policymakers and businesses in improving the various entrepreneurial aspects of informal community entrepreneurs in developing countries.Originality/valueIn the authors’ knowledge, this is unique research on marginal women entrepreneurs in Bangladesh.

Roleplay: A Tool for Engaging English Language Learners

This article examines the advantages of incorporating roleplay into academic environments, with a specific emphasis on its ability to improve communication and promote the acquisition of vocabulary among students. The study explores the design concerns and assessment methodologies used in roleplay exercises in academic settings, emphasising their efficacy in fostering critical thinking, argumentation skills, and a profound comprehension of course material. The study investigates the impact of roleplay activities on learners' readiness for real-life business interactions, acquisition of negotiation skills, and improvement of professional communication in business environments.

DRA Global: implementing digital transformation through change management in a project consultancy firm

Learning outcomes After reading and discussing the case study, students should be able to identify the reasons why the company needed to digitise and how this links to the company’s strategy around technology and innovation, analyse the digitalisation implementation process followed in the case study by using an organisational change management model and make recommendations and propose a solution for the protagonist to consider for the successful roll-out of the digitalisation project. Case overview/synopsis DRA Projects is part of the DRA Global business based in South Africa. The company is known locally in the mining and engineering industry for its project development, delivery, execution and operations capabilities. Digital transformation is a key strategic focus in the industry, as clients seek digitised integrated systems. For this client offering, J.C. Heslinga, managing director of DRA Projects, was tasked with leading the digitalisation of the project delivery system. From July 2020 until July 2022, Heslinga led the implementation team through different organisational change stages. As the next phase included rolling out digitalisation to pilot projects and engaging employees and clients in the new process, Heslinga wondered if enough was done to ready the business for this change. The end users would be executing the changes, so their adoption will be imperative for successfully rolling out digitalisation. The case study concludes with Heslinga pondering the approach needed for the next phase. The case study focuses on the digitalisation implementation process through the lens of organisational change. The case study presents an opportunity to analyse and identify the theories and models used in organisational change within a real-life business context. The organisational change learnings can be adapted to help students with any transformation changes in similar business scenarios. Complexity academic level Postgraduate- and master’s-level students and business executives attending short courses will benefit from the learnings. The learnings can be applied to improve decision-making, organisational behaviour and strategic implementation using the fundamental principles of organisational change. Supplementary materials Teaching notes are available for educators only. Subject code CSS 6: Human resource management

Design Thinking in the Executive MBA

This article describes the redesign of a Strategic Vision course in an Executive Master of Business Administration (EMBA) program in the United States, and the subsequent use of design thinking as a critical problem-solving tool in the program itself. Using Design Thinking as the curricular framework, this experiential course aims to introduce business executives to solving business challenges through design thinking methodologies. Over eight weeks, student teams work with external project partners to produce creative business solutions to current and complex organizational challenges. Teams are introduced to Design Thinking and practice steps in the Design Thinking process by applying them to a real-life business challenge. Here, we describe the genesis of the course redesign, iterations on its content, and the feedback it has received from students, faculty, and project partners, in the hope that it will contribute to the curation of new design frameworks in higher education.

AIMED: An automatic and incremental approach for business process model repair under concept drift

Real-life business processes may change over time in response to new business requirements, market changes, new policies or regulations, etc., which is called concept drift in the data mining area. How to identify and deal with the concept drift problem is a significant challenge in business process mining. Currently, the research mainly focuses on the problems of concept drift detection. However, the proposed approaches do not intuitively explain how the process changes. In this paper, we provide an integrated framework whose core technique is an Automatic and Incremental approach for business process Model rEpair under concept Drift (AIMED). AIMED streamlines the functions of concept drift detection, localization and model repair. More specifically, when concept drift is detected, it updates the process model automatically by precisely localizing the sub-structure of the process model that concept drift affects and updating this sub-structure accordingly. Concept drift is explained intuitively by presenting the repaired model. In particular, AIMED can resist the noise that greatly affects the performance of current concept drift detection and process model repair techniques. The properties of AIMED are theoretically proven. We also conduct extensive experiments on synthetic logs as well as real-life logs. The experiment results show that AIMED outperforms the state-of-the-art methods in both concept drift detection and process model repair and works well even when there is noise in logs.

A framework for modeling, executing, and monitoring hybrid multi-process specifications with bounded global–local memory

So far, approaches for business process modeling, enactment and monitoring have mainly been based on process specifications consisting of a single process model. This setting aptly captures monolithic scenarios from domains in which all possible behaviors can be folded into a single model. However, the same strategy cannot be applied to domains where multiple interacting (procedural) processes simultaneously work over the same objects, in the presence of additional (declarative) constraints relating activities from the same or different processes. A relevant example for this setting is that of healthcare, where co-morbid patients may be subject to multiple clinical pathways at once, in the presence of additional, general constraints capturing basic medical knowledge. To fill this gap, we have previously presented the M3 Framework and an accompanying monitoring technique, which allows for a hybrid representation of a process using both procedural and declarative models, and supports the modular creation of multi-process specifications where domain experts can focus on specific procedures and domain constraints without being forced to merge them into one single specification. In this paper, we make significant extensions to this framework, allowing us to go from simple toy examples towards addressing practical real-life scenarios. We achieve this by introducing a richer form of integration between the interacting process components, in particular supporting asynchronous and synchronous activities that may operate over local and global (shared) data variables. This is framed by a discussion of the business meaning of these concepts, the introduction of the corresponding modeling patterns, and the application of our approach to real-life business processes, the latter being the driving-force behind this paper.

Digitalization of management systems in retail industry: Russia in the context of global transformation

Digitalization today is one of the most relevant trends on Russian and world retail market that has repeatedly proven its efficiency not only in communications with consumers and store-level operations but also in organizational management. The purpose of the study is to conduct a comparative research of Russian and foreign practice of integrating digital technologies in management systems. The analysis has been based on author’s own model – “technology – management area” matrix – developed through a review of normative and scientific literature. It also has been carried out for ten largest retailers in Russia and ten ones in the world. As a result of the study, key current areas of management systems’ digitalization have been identified for both Russian and foreign retailers. Those areas between the ones, in which Russian companies have already reached global benchmarks, and the ones, in which Russian retail still retains potential for future development, have been distinguished. Recommendations for management systems’ digitalization in retail industry formulated by the author following the results of the analysis can be successfully used not only in research and methodological purposes but also in real-life business practice to increase efficiency of the process concerned.

Developing a Strategic Cost Management Model for a Potato Packing Facility

Purpose: The purpose of the study was to solve a real-life business problem by developing a new customised strategic cost management (SCM) model for the case study entity － a South African potato packing facility. Design/method/approach: The study followed a pragmatic philosophy where data were collected by observation and semi-structured interviews. The data focused on the following SCM techniques: Business process re-engineering, activity-based management, Kaizen costing, total quality management, and target costing. Findings: The investigation found that, except for target costing, all the SCM techniques belong in a SCM model. The investigation also revealed specific practical operational examples which were firstly analysed according to codes, and secondly aggregated, rewritten, and inductively reasoned in order to illustrate these processes in a new customised SCM model. Practical implications: After the operational processes were documented, a new customised SCM model was developed for the case study entity. The findings of the study could be helpful when other organisations manufacture, process, or pack various products to make informed management decisions. Originality/value: The value of the study lies in the likelihood to establish transferability － the process that was followed to develop a new customised SCM model could be replicated.

Application of Simulation Modeling as a Teaching Pedagogy in Business Education

Simulations in higher education serve as an effective pedagogical tool to surge learners’ motivation and support in harnessing 21st-century skills. However, the cost of the software required expertise, and its complexity is some of the deterrents to its smooth adoption. It rarely allows you to learn what is happening in the background. How are the decision variables linked and affected? This research proposes and tests system dynamic (SD) based simulation modelling based on Sterman (2000) to investigate the use of simulation as a pedagogy to showcase growth in population(demand-side), its relationship to residential construction (supply-side), and finally predicts the total residential construction spending. The simulation case depicts a real-life business scenario where users are able to dynamically vary the decision variable values, and visualize its effect on dependent variables and the overall impact on the simulation goal. Even students and non-Economist can efficiently perform quality analyses for experiential learning.

Green vehicle routing and dynamic pricing for scheduling on-site services

In this paper, we study a problem where a company sends engineers with vehicles to customer sites to provide services. Customers request the service through a website or by calling a call centre and the company needs to allocate the service tasks to time windows and decide on how to schedule these jobs to their vehicles. We propose a new approach to this problem which applies low-emission vehicle routing techniques with dynamic pricing to reduce CO 2 emissions and maximise profit. When a customer requests a service, the company will provide the customer with different service time-window options and their corresponding prices. Prices are differentiated to influence the customer's choice. To help the company in determining the prices, our approach solves the problem in two phases. The first phase solves a time-dependent vehicle routing model with the objective of minimising CO 2 emissions for each of the time window options and the second phase solves a dynamic pricing model to determine the service prices for these options to maximise profit. Metaheuristic methods are applied for real-life business applications which enable the solution framework to be applied online where shorter computational time is required. The approach is tested through numerical experiments. Results show that dynamic pricing leads to a reduction in CO 2 emissions and an improvement in profit.

Using Padlet as a Learning Space for Simulating Real-Life Business Communication

Due to the Covid-19 pandemic, lecturers of higher learning institutions had to pivot quickly from face-to-face classes to online classes. The new normal of online teaching and learning challenged lecturers in keeping their students engaged, especially when teaching a language course that heavily focuses on the writing component. The purpose of this study was to examine students’ perception of using Padlet as a learning space to simulate real-life business communication. At the end of a 14-week semester language course, a cohort of 38 diploma students responded to a self-administered online survey with a 79% response rate. Findings from the descriptive analysis indicated high mean values for most survey items measured, implying that the students were generally favourable towards the use of Padlet and the simulation approach in learning business communication. Curriculum designers and lecturers of other courses could consider the potential of using Padlet as a learning space for simulation. Recommendations, limitations, and future research directions are also discussed in this paper.

Discovering Structural Errors From Business Process Event Logs

Process mining aims at discovering behavioral knowledge of business processes from their event logs, which has received an increasing attention in the era of cloud computing and big data. Surprisingly, to date, discovering structural errors (e.g., deadlocks and lack of synchronization) from event logs has not been considered in state-of-the-art process mining techniques. Moreover, existing process discovery approaches cannot be directly applied to event logs of processes with structural errors due to erroneous event occurrences caused by unsynchronized activities. To address this problem, we first preprocess the event log to obtain two separate event logs that are used to discover deadlocks and lack of synchronization, respectively. Erroneous event occurrences caused by unsynchronized activities are discarded in the two processed event logs, from which our error mining algorithms can discover all process fragments involving structural errors, without the need to obtain the overall process first. We implement our approach in a ProM plugin and evaluate it on event logs of real-life business processes, the results of which demonstrate that our approach can effectively and efficiently discover deadlocks and lack of synchronization if event logs contain sufficient event sequences.

The Global Case Study Challenge: A Virtual Exchange Developing Global Work Competencies

The Global Case Study Challenge (GCSC) is a virtual exchange program designed for Bachelor and Master level students from interdisciplinary programs. The program focuses on the development of key Global Work (GloW) competencies, defined as: intercultural, digital communication and sustainability competencies. This paper discusses how the GCSC, as a new virtual model of teaching and learning, in a real-world context, supports the development of future-oriented work competencies. These competencies are crucial for effective global virtual teamwork and New Work scenarios in remote contexts. To date, 1450 students and 50 educators from 30 universities across 20 different countries have worked together in some 380 Global Virtual Teams on real-life business cases. 
 The learning design of this virtual exchange project is rooted in the knowledge that future-oriented global work competencies such as intercultural competence, digital communication competence and sustainability competence can only be developed through transformative learner-centred experiential learning. In the 2021 iteration of the GCSC, over the 8-weeks of the program, 86 groups of interdisciplinary Global Virtual Teams (GVTs) worked together: Establishing team-building dynamics while working in self-directed GVTs of 5-7 students, reflecting on (corporate) sustainability, collaborating on real-life business cases, and presenting their solutions and recommendations to a major global corporate partner at a virtual conference. The impact of the program on students’ competency development was measured using a longitudinal study design. The intercultural, digital communication, and sustainability competencies of the participants were measured pre-exchange (n=263) and post-exchange (n=274). The findings demonstrate a consistent increase of competencies over time among the program participants in almost all categories (knowledge, skills, attitudes), providing clear evidence of the overall positive impact of the GCSC on participants' competency development over the two-month program. Ultimately, the GCSC contributes towards students becoming highly effective members and leaders of high-performing Global Virtual Teams.

Design Science Research Framework for Performance Analysis Using Machine Learning Techniques

We propose a methodological framework based on design science research for the design and development of data and information artifacts in data analysis projects, particularly managerial performance analysis. Design science research methodology is an artifact-centric creation and evaluation approach. Artifacts are used to solve real-life business problems. These are key elements of the proposed approach. Starting from the main current approaches of design science research, we propose a framework that contains artifact engineering aspects for a class of problems, namely data analysis using machine learning techniques. Several classification algorithms were applied to previously labelled datasets through clustering. The datasets contain values for eight competencies that define a manager’s profile. These values were obtained through a 360 feedback evaluation. A set of metrics for evaluating the performance of the classifiers was introduced, and a general algorithm was described. Our initiative has a predominant practical relevance but also ensures a theoretical contribution to the domain of study. The proposed framework can be applied to any problem involving data analysis using machine learning techniques.

Transformer Networks and Their Real-World Business Applications

Recent advances in deep learning models have presented many opportunities for businesses. This article focuses on the possible game changing development of transformer networks which have enabled self-supervised learning. These advances provide encouraging opportunities for business applications. The article discusses the different types of learning paradigms and the similarities and dissimilarities between them. The article also discusses how transformer networks enable self-supervised learning. The article finally discusses real-life business applications with data from text, audio and images.

Modelling Cost of Quality for Defect Reduction

Purpose: This paper aims to develop the system dynamics model of managing quality costs using the perception maps prepared on the basis of the actual data of the organization. The model depicts the cost of quality and the associated defect percentage to represent the real-world data of the company under study. Model is validated using the different tests to build the confidence on the model. Underlying feedback structures and interactions among various variables make the model more robust and realistic.
 Design/Methodology/Approach: The simulation software STELLA is used for programming the model. Using the generic structures of the cost of quality, stock and flow diagram is developed to map the real-life business scenario.
 Findings: Cost of Quality is a forgotten dimension in many companies. Most of the companies are not measuring the cost of quality as a powerful indicator for quality measurement and for process improvement. Defect level is the function of prevention, appraisal and failures (PAF) costs associated with the PAF model. System Dynamics is computer-based simulation methodology that gains the insight of the social, economic, and business problems and acts as a powerful tool for policy design for better decision making.
 Implications/Originality/Value: Policy analysis clearly indicate that dynamics of cost of quality is quite complex and to identify the prioritized parameter for investment cannot be intuitively appreciated. System dynamics is a simulation-based methodology which can solve the complex interactions and different policy runs lead to the best appropriate mix of cost elements in order to reduce the failure costs (internal and external).

The antecedents and outcomes of export market orientation: A bibliometric review

Export market orientation has always been a central issue in the study of international business and marketing. Therefore, it is essential to put effort into understanding the concept and its application in real-life business. Following in-depth studies and critical review papers in previous years, this research paper focuses on synthesizing and analyzing empirical studies in the period from 2015 to 2021, revolving around theoretical issues, context, the main features of the object, and the methodology. Within a predetermined time frame, twenty critical papers on export market orientation were selected and analyzed. The result reveals in detail that there are sixteen antecedents and five outcomes of export market orientation, as well as the total of eight moderators and seven mediators influencing their relationships. Findings have indicated that in recent years, models and theories of earlier eras have been developed and many of them have reached maturity.

Full curriculum-based venture creation programmes: current knowledge and research challenges

PurposeFull curriculum-based Venture Creation Programmes (VCPs) are a relatively new and potentially underutilised form of degree programme in which students explore the on-going creation of a new venture as a primary aspect of their formal study. The highly experiential nature of VCPs has the potential to meet the calls of researchers and policymakers for students to actively participate in and control their own learning for enterprise and entrepreneurship. However, research into VCP's remains limited which constrains their development. The purpose of this paper is, therefore, to review the literature surrounding VCPs in order to investigate the current research and explore areas for further study to support the development of these courses.Design/methodology/approachA systematic literature review was conducted in order to find and explore literature around VCPs, defined here as credit-bearing whole programmes of study, focused on learning for entrepreneurship, with the creation of a real-life business venture as an integral part of the learning experience, on which completion of the programme is dependent. First, academic literature published in peer-reviewed journals was collected through a systematic search. In parallel with this, academic colleagues working in this space were contacted for recommendations of literature and for information on work in progress. This led to additional emerging work being discovered that is primarily being presented at conferences. A further general Internet search was conducted to find non-academic information, reports and literature relating to VCP practice.FindingsFour themes were explored covering the entire student journey (1) application and recruitment; (2) teaching, learning and assessment; (3) development of entrepreneurial identity; and (4) entrepreneurial outcomes. The literature presented in the paper suggests that VCPs can meet calls to provide an innovative curriculum based on experiential learning principles. VCPs can provide a positive learning experience in addition to leading to actual business start-up during the degree or after graduation.Originality/valueThis paper presents a comprehensive review of literature focusing on VCPs. Recommendations are made for further research. A key question remains: if full VCPs have the potential to enhance learning, produce positive business outcomes, and address policy calls, why are there so few known VCPs at universities around the world?

RETRACTED ARTICLE: Sentiment analysis using treebank filtered preprocess with relevant vector boost classifier

The procedure of identifying and classifying opinions in a piece of text to find out whether customer reviews toward a particular product or service are positive, negative, or neutral is termed as sentiment analysis. Stock market prediction is one of the most attractive topics in academic and real-life business. Many data mining techniques about sentiment analysis are suffering from the inaccuracy of prediction. The low classification accuracy has a direct effect on the reliability of stock market indicators. Treebank filtering Data Preprocessing based Ochiai-Barkman Relevance Vector Linear Programming Boost Classification technique is used for stock market prediction using sentimental analysis with higher prediction accuracy and lesser classification time for enhancing accuracy of stock market based on product review. Initially, the customer reviews and feedback on services or products are collected from the large database. After that, the collected customer reviews are preprocessed by performing the process such as tokenization, stemming, filtering. In order to achieve sentimental analysis through classifying customer reviews as positive and negative, Ochiai-Barkman Relevance Vector Linear Programming Boost Classification algorithm is used. The Linear Programming Boost Classification algorithm constructs with an empty set of weak classifiers as the Ochiai-Barkman Relevance Vector machine. The customer reviews are classified based on the Ochiai-Barkman similarity coefficient. The ensemble technique combines the weak classification results into strong by minimizing the error. In this way, the classification performance gets improved and the prediction of the stock market is carried out in a more accurate manner. Experimental evaluation is carried out on factors such as prediction accuracy, sensitivity, specificity, and prediction time versus amount of customer reviews.