Retail Companies Research Articles

Post-Pandemic Financial Distress Analysis: A Study of Retailer and Tourism Companies Listed in Bursa Malaysia Using the Grover Model

A corporation enters financial distress when its cash flows are insufficient to cover its debts to stakeholders, both financial and non-financial. When the Coronavirus Disease 2019 (COVID-19) pandemic struck the world and caused lockdowns that impacted many businesses, particularly those in the tourism and retail industries, the likelihood of financial distress increased. Thus, the Grover model is used to determine and analyse the financial distress prediction in retail and tourist companies listed on Bursa Malaysia. The Grover model categorises companies as financially distressed with a G-Score equal to or less than -0.02. Meanwhile, the G-Score for companies in the safe zone is equal to or greater than 0.01. Four companies were chosen, and a sample of data was collected from 2017 to 2021. The findings showed that during the COVID-19 pandemic from 2020 to 2021, three companies were under financial distress, especially those in the tourism and hospitality sectors. Meanwhile, retailer companies, especially those in food manufacturing, were not affected by this pandemic.

The Algorithm and the Org Chart: How Algorithms Can Conflict with Organizational Structures

Algorithms are introducing changes to individuals? jobs, but do algorithms also lead to changes in the structures of organizations themselves? Organizational structures, as often formalized into organization (org) charts, are meant to facilitate coordinated decision-making. Yet our 10-month ethnographic study of a large online retail company reveals why the organizational structures that facilitate effective decision-making by humans may be in tension with the organizational structures that facilitate effective decision-making using algorithms. Our findings show that the human decision-makers needed small, divided-up sets of decisions, and they had previously accomplished this through how they structured individuals' roles and teams in the org chart. In contrast, when data scientists developed a new algorithm and first deployed it within organizational structures meant to support human decision-making, they realized that these small divided-up decision spaces were arbitrarily constraining the algorithm's search space. When not constrained in this manner, the algorithm could identify and recommend better solutions, but those optimal solutions did not always align with the structure of roles and teams in the org chart. This study suggests that as algorithms are integrated into the workplace, organization designs may begin to more explicitly reflect the contours of those algorithms' behaviors.

Analisis Pengaruh Kelengkapan Produk dan Promosi Penjualan Terhadap Keputusan Pembelian Konsumen di Transmart KarawanG

The research was conducted at Transmart Karawang. In the current era of globalization, demand from consumers is increasing so as to provide profitable potential for the business world. A survey was conducted on the customer value index of 10 stores in Indonesia, one of the retail companies that is experiencing these problems is Transmart which occupies the fourth position. Reporting from kompas.com, it is said that at least 12 Transmart outlets will be permanently closed throughout 2022. The problem of declining sales levels at Transmart Karawang, as evidenced by the decreasing number of customers visiting the store, is the main subject of this study. This phenomenon is believed to arise due to consumer skepticism about their purchasing choices, which are influenced by product completeness and sales promotions. The purpose of this observation is to understand how product completeness and sales promotion affect consumer purchasing decisions at Transmart Karawang. Translated with DeepL.com (free version)The subjects of this research are consumers or customers of Transmart Karawang. The research methodology used quantitative and survey methodologies. The applied data sources include main data and supporting data, while the applied data collection techniques include questionnaires, face-to-face interactions, observations, and literature studies. A research sample of 99 respondents was selected from a population of 8422 using the Slovin formula. This research utilizes multiple linear regression analysis methodology using SPSS version 27.0 software to evaluate the effect of product completeness and sales promotion on purchasing decisions at Transmart Karawang. The research findings show that 82.9% of consumers in Transmart Karawang are influenced in their purchasing choices by the presence of product completeness and purchase promotions. A total of 17.1% of the evaluation was influenced by unresolved issues in this study.

E-Business and supply chain integration is the ultimate online shopping

E-business has risen as a key empowering influence to drive supply chain integration. Organizations can use the internet to achieve worldwide visibility on their extended trading network. The influence of e-business on supply chain integration can be defined laterally the dimensions of information integration, synchronized planning, coordinated workflow, and new business models. An Important value can be added to e-business by enabling supply chain integration. In this report, the author has taken a popular rising e-commerce company from Bangladesh. The name of this company is AJKERDEAL. It is a Bangladeshi online retail company, that focuses on a low-cost-oriented supply chain to maintain cost efficiency. The company's success is attributed to its superior supply chain practices over local competitors. However, Western multinational retailers may struggle in Bangladesh due to their differing values, cultures, and beliefs, potentially jeopardizing their key market.

Digital Transformation Strategies for Enterprises - An Case Study of the Traditional Retail Industry

Against the background of rapid changes in science and technology and the rapid development of the digital economy, the market landscape is going through unprecedented and profound changes, consumer preferences becoming more and more personalized and diversified, while the e-commerce sector has shown a vigorous development trend. More and more traditional retail companies realize that digital transformation has become an unavoidable trend under competitive pressure. How traditional retail companies can establish a competitive and adaptable business model through digital technology is an urgent problem that needs to be solved nowadays, but many companies have no clear idea about it and lack systematic digital transformation plans. This paper analyses the current situation of traditional retail enterprises and the dilemma of digital transformation. It puts forward suggestions for digital transformation strategies, hoping to help retail enterprises understand and cope with the challenges of digital transformation, enrich the ideas of digital transformation at the theoretical level, and provide references for traditional retail enterprises that are undergoing digital transformation.

Increasing The Effectiveness And Efficiency Of Local Msme Consignment Cooperation With The Vendor System

MSMEs have an important role in the Indonesian economy but face challenges in adapting to the digital era and establishing effective collaboration with retail companies. This research aims to develop and evaluate a vendor portal system that can overcome this challenge by increasing the effectiveness and efficiency of consignment collaboration between local MSMEs and retail companies. Using qualitative descriptive methods, this research analyzes the impact of implementing a vendor portal system on consignment business processes, including operational efficiency, transparency, and collaboration between both parties. The research results show that the vendor portal system has succeeded in increasing operational efficiency, providing real-time transparency of sales and inventory data, and facilitating better communication between MSMEs and retail companies. Apart from that, this system also supports government programs in encouraging MSMEs to "Go Digital" and "Upgrade"

Analisis Segmentasi Pelanggan Berbasis RFM dan Evaluasi Efektivitas Kampanye Pemasaran untuk Meningkatkan Retensi

This research implements RFM (Recency, Frequency, Monetary) analysis to perform customer segmentation and evaluate the effectiveness of marketing campaigns in a retail company. Using a Kaggle dataset, this study identifies customers based on purchasing behaviour and assesses marketing campaign responses for each segment. The analysis reveals that Loyal, VIP, and New Customer segments showed the highest responses, especially in Campaign 6. The findings emphasize the importance of targeting resources on effective segments and campaigns to optimize marketing strategies and maximize ROI. Personalized campaigns based on segmentation can enhance customer retention and align product offerings with customer needs.

APPLYING SOFT COMPUTING METHODS IN BUSINESS ANALYTICS USING HYBRID GENETIC ALGORITHMS

In the era of big data and advanced analytics, the application of soft computing techniques has emerged as a powerful tool in solving complex business problems. This paper presents the use of hybrid genetic algorithms (HGAs) in business analytics to address challenges related to optimization, prediction, and decision-making processes. Traditional algorithms often struggle with large, nonlinear, and dynamic datasets typical of business environments. The incorporation of soft computing techniques such as genetic algorithms (GAs) and their hybridization with other methods like fuzzy logic and neural networks can help overcome these limitations. The problem addressed in this research is optimizing decision-making in marketing strategies, focusing on maximizing return on investment (ROI). Standard methods face difficulties in navigating through vast datasets and discovering optimal solutions. The hybrid genetic algorithm proposed in this study combines the exploration strength of GAs with the exploitative precision of local search techniques. The model was tested using a real-world dataset of marketing expenditures and revenues from a retail company. The HGA achieved an ROI improvement of 25%, significantly outperforming standard GAs and traditional optimization methods, which yielded only a 12% improvement. The flexibility and efficiency of this approach make it ideal for various business applications, including supply chain optimization, customer segmentation, and product pricing.

Analysis Of Bankruptcy Prediction Using Springate, Zmijewski, Grover. And Altman Z-Score Models On Retail Companies Listed On The Indonesia Stock Exchange

The retail sector plays a significant role and contributes greatly to the national economy. The slowdown in domestic economic growth and decreased consumer purchasing power have significantly impacted the retail business in Indonesia. This is evident from the high number of retail companies declared bankrupt and many large retail companies closing their stores. The aim of this study is to assess the health level of retail companies, determine the differences in scores among the research models, and evaluate the accuracy of the Springate, Zmijewski, Grover, and Altman models. This research is a quantitative study with a descriptive approach. The research objects are retail companies listed on the Indonesia Stock Exchange during the period 2019-2021. Sampling technique used is purposive sampling. The results of this study indicate that the highest accuracy level is achieved by the Grover model with an accuracy of 77.7%, followed by the Zmijewski model with an accuracy level of 72.2%. Meanwhile, the Springate and Altman models have the same accuracy level of 66.6%.

The Effect of Compensation, Organizational Culture, and Rewards on Employee Productivity in Retail Companies in Indonesia

This study examines the effect of compensation, organizational culture, and rewards on employee productivity in retail companies in Indonesia. Using a quantitative research design, data were collected from 140 retail employees and analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS 3). The findings reveal that compensation, organizational culture, and rewards all have significant positive effects on employee productivity. Compensation emerged as the strongest predictor, followed by organizational culture and rewards. These results suggest that fair compensation, a supportive organizational culture, and effective reward systems can significantly enhance employee performance in the retail sector. The study provides practical recommendations for retail companies to improve workforce productivity through strategic human resource management.

Evaluation of Financial Performance with the Balanced Scorecard Approach in Retail Companies

This research assesses the financial performance of retail enterprises utilizing the Balanced Scorecard (BSC) methodology. The study used a quantitative methodology, gathering data from 75 retail firms via a Likert-scale questionnaire (1 to 5). The analysis use SPSS version 26, concentrating on four key Balanced Scorecard perspectives: financial, customer, internal business processes, and learning and growth. The findings indicate substantial positive relationships across the customer, internal processes, and learning and growth perspectives with financial success, with the customer viewpoint serving as the most robust predictor. The results indicate that retail firms can improve financial performance by prioritizing customer satisfaction, operational efficiency, and ongoing innovation. These insights offer significant recommendations for retail managers seeking to synchronize strategic objectives with operational performance.

Borsa İstanbul’da faaliyet gösteren perakende firmalarının pazarlama harcamalarının firma performansı üzerindeki etkileri

This study aims to find the factors that affect the sales revenues and asset profitability of companies operating in the retail sector. The study consists of retail companies listed on Borsa Istanbul, covering the quarter periods between 2015/3 and 2022/9. In the sample, as of 2022, 14 companies are traded in the retail sector on the stock exchange. Since the data of 6 companies among these companies could not be accessed, they could not even be analysed, and analyses were made on the panel data created with eight companies whose data had the desired characteristics. Regression and correlation tests were performed in the analyses. The panel data obtained from the sample were analysed using Stata 13.0 and EViews 9 package programs. According to the results of the analysis, it has been determined that marketing, sales, and distribution expenses impact sales revenues, while general administrative expenses and advertising expenses impact return on assets (ROA).

Bankruptcy Analysis Using the Altman Z-Score Model (Study on Retail Companies Listed on the Indonesia Stock Exchange)

Bankruptcy is a legal or economic event that often results in the complete cessation of all business activities and operations. This bankruptcy usually starts with liquidity problems, but is closely linked to situations where a company's debt exceeds its total assets. The objective of this study is to evaluate the effectiveness of the Altman Z-score model as a tool to predict bankruptcy. The main focus of this study is retail companies listed on the Indonesia Stock Exchange in 2021-2023. 31 companies participated in the study, supported by 93 financial statements. The researchers used purposive sampling method for the sampling process. The study uses the modified Altman Z-score method (1995) to analyze the obtained data. The analysis revealed that 17 companies (54.8%) could be classified as healthy. 3 companies (9.7%) were classified as weak, and 11 companies (36.7%) were expected to go bankrupt. These results provide insight into the financial health of the retail companies surveyed and highlight the importance of using predictive models to determine bankruptcy risk.

Food and beverage manufacturing and retailing company policies and commitments to improve the healthfulness of Canadian food environments

BackgroundFood and beverage companies play a central role in shaping the healthfulness of food environments.MethodsThe BIA-Obesity tool was used to evaluate and benchmark the specificity, comprehensiveness and transparency of the food environment-related policies and commitments of leading food and beverage manufacturing and retailing companies in Canada. Policies and commitments related to the healthfulness of food environments within 6 action areas were assessed: 1) corporate nutrition strategy; 2) product (re)formulation; 3) nutrition information and labelling; 4) product and brand promotion; 5) product accessibility; and 6) disclosure of relationships with external organizations. Data were collected from publicly available sources, and companies were invited to supplement and validate information collected by the research team. Each company was then assigned a score out of 100 for each action area, and an overall BIA-Obesity score out of 100.ResultsOverall BIA-Obesity scores for manufacturers ranged from 18 to 75 out of 100 (median = 49), while scores for retailers ranged from 21 to 25 (median = 22). Scores were highest within the product (re)formulation (median = 60) followed by the corporate nutrition strategy (median = 59) domain for manufacturers, while retailers performed best within the corporate nutrition strategy (median = 53), followed by the disclosure of relationships with external organizations (median = 47) domain. Companies within both sectors performed worst within the product accessibility domain (medians = 8 and 0 for manufacturers and retailers, respectively).ConclusionsThis study highlights important limitations to self-regulatory approaches of the food and beverage industry to improve the healthfulness of food environments. Although some companies had specific, comprehensive, and transparent policies and commitments to address the healthfulness of food environments in Canada, most fell short of recommended best-practice. Additional mandatory government policies and regulations may be warranted to effectively transform Canadian food environments to promote healthier diets and prevent related non-communicable diseases.

Work dynamics in retail industry: Impact of work intensification, high-performance work systems, and emotional exhaustion

The retail industry has complex and demanding work dynamics. In this context, a deep understanding of the factors that influence employee performance is highly relevant to managing retail companies. This study examines the interrelationships among work intensification, high-performance work systems (HPWS), emotional exhaustion, employee creativity, and employee performance within the retail industry. This study used a survey approach with a quantitative methodology; data were gathered through questionnaire distribution to 235 retail employees across Jakarta, Indonesia, utilizing non-probability convenience sampling. Analysis was conducted using partial least squares-structural equation modeling (PLS-SEM) via the SmartPLS version 3.3.3 tool. Results revealed that work intensification significantly and positively influences HPWS and emotional exhaustion (p < 0.05). While HPWS exhibited no significant impact on employee creativity, emotional exhaustion had a significant and negative effect (p > 0.05). Furthermore, employee creativity demonstrated a significant positive effect on employee performance (p < 0.05). It was a significant mediator between emotional exhaustion and employee performance, though not between HPWS and employee performance (p < 0.05). The study underscores the intricate dynamics within the retail work environment, highlighting the intertwined roles of HPWS, emotional exhaustion, and employee creativity. Practical implications emphasize the necessity for effective management strategies to navigate work intensification and emotional exhaustion, ultimately enhancing employee performance. Notably, this paper offers a comprehensive analysis of factors shaping employee performance in the retail sector, emphasizing the pivotal significance of HPWS, emotional exhaustion, and employee creativity as interconnected components.

A Semantic Analysis of the User-Generated Content from Social Network Sites of Cashbuild Limited: Application of Text Mining, Machine Learning and Big Data Analytics toward the Development of a Customer-Centric Marketing Strategy

Social Network Sites (SNS) have grown rapidly over the past 15 years, which is in line with the growth of smartmobile phones. A key phenomenon of SNSs is User-Generated Content (UGC). It enables social engagements between users and their followers. UGC shares various perspectives on news, entertainment, and fun, as well as their perspectives on brands like Customer Experience (CX) and Customer Satisfaction (CS). UGC stimulates the Brand Attitudes (BA) of the readers if the user is trusted and credible. BAs influence the Purchase Intentions (PI) of the readers of UGC. Marketers like that UGC influences PI. They learn about CX and CS, which users share on the UGC. This semantic study uses Text Mining (TM) and Big Data Analysis (BDA) to extract keywords from the UGC of a building materials retail company, Cashbuild Limited (CBL) from the Republic of South Africa (RSA). The UGC was analysed using Power BI (PBI) to identify its sources and sentiments. The majority of the UGC in this study was obtained from Facebook (94.51%), followed by X.com (3.95%). The rest of the UGC was obtained from Blogs (0.79%) and Instagram (0.76%). 65.63% of the UGC was neutral, 29.74% positive, and 4.46% negative. UGC influences PI by mediating hedonic and utilitarian Brand Equity. The generation of a high-quality UGC was encouraged by CS - an outcome of CX. CX comes from the touchpoints across the CJ. Marketers want to ensure a good customer experience (CX) to achieve customer satisfaction (CS). Ultimately, CS influences future customer expectations (CE) when shared through UGC. 84 top keywords were extracted out of 16 328 hit sentences (HS) from the UGC of CBL using the MELTWATER program. The keywords were ranked to 51 frequency positions. CONCOR analysis was used to determine the connectivity and centrality of the keywords using Freeman’s coefficient and the Eigenvector value for each keyword. The results of the CONCOR analysis were used to identify 41 significant keywords based on their higher connectivity and centrality. The 41 significant keywords were matched with the 16 328 HSs. 14 keywords that matched less than 100 HSs were excluded. The remaining 27 keywords were subjected to exploratory factor analysis EFA on Statistical Program for Social Sciences (SPSS). 21 keywords were loaded on 8 factors, and the model explained 68.363% of the variance with a Kaizer Meyer Olkin (KMO) of 0.736 above 0.6. The 8 categories were compared to input from a panel of industry experts. 7 categories proposed by experts matched 7 out of 8 categories from the statistical model. 7 key themes proposed to be used in the study to develop Customer-centric Marketing Strategies (CCMS) in the building materials retail industry (BMRI) are DIY Kings, House Proud, Project Master, Renovators, Interior Image, Building Materials Inventory, and Promotions. All 5 objectives of the study were met. The study adds value to the development of CCMS learning from the UGC.

RUSSIAN RETAIL TRADE IN RUSSIAN FEDERATION: CURRENT STATE

The present paper contains a description of article the current state of the retail market in the Russian Federation. The main trends of the development of retail in Russia are shown. These trends include the growth of digital retail, the emergence of new retail formats adapted to the changing purchas-ing power of the population, the entry of federal retail operators into new regional markets and the acquisition of small retail companies by large chains. A major threat to the sustainable development of retail may be a shortage of labor, which requires a revision of the policies of retail companies in the field of personnel management.

The Role of Leadership in Transforming Retail Technology Infrastructure with DevOps

In the fast changing retail technology market, DevOps principles are transforming how firms manage and improve their technological infrastructure. This study examines how leadership may use DevOps to improve retail technology and operations. As retail embraces digital transformation, technological strategies must fit with business goals. This change requires leaders to guide their firms through complicated infrastructure upgrade and operational efficiency. DevOps, which emphasizes communication between development and operations teams, continuous integration and delivery, and automation, has become essential for technological infrastructure agility and efficiency. DevOps benefits retail companies in a competitive world with quick customer behavior and market fluctuations. These include increased deployment frequency, time-to-market, dependability, and scalability. DevOps demands a fundamental change in corporate culture and leadership, not simply new technologies and procedures. This article discusses how successful leadership can promote collaboration, transformation, and DevOps alignment with strategic corporate objectives to achieve this cultural transition. Leadership helps overcome change resistance, foster cross-functional cooperation, and incorporate DevOps into the organization's technology and business operations. Leaders must also address talent shortages, resource limits, and outdated systems that might hinder DevOps rollout.

The Effect of Good Corporate Governance and Capital Structure on Firm Value with Financial Performance as an Intervening Variabel

With financial performance serving as an intervening variable case study of retail companies listed on the Indonesia Stock Exchange in 2019–2022, the goal of this research is to ascertain the impact of sound corporate governance and capital structure on firm value. There were forty-two retail companies in the study's population. Of the 42 companies that used the purposive sampling approach for sample withdrawals, 29 of them satisfied the sample requirements. Secondary data was obtained by obtaining the annual report of the firm via the website of the Indonesia Stock Exchange or the company itself, together with the documentation data gathering process. Using SmartPLS software, the partial least square (PLS) analysis of structural equation modeling, which is component- or variance-based, is combined with descriptive analysis to analyze the data. The findings demonstrated that capital structure and sound corporate governance both have an impact on a company's value. Financial performance is not able to mediate the relationship between excellent corporate governance and capital structure on company value, but neither do good corporate governance nor capital structure have any effect on financial performance.

Voluntary turnover of high achievers: A systems psychodynamics analysis with CIBART

Orientation: Voluntary turnover is a costly and frequently disruptive organisational phenomenon, particularly when it involves high achievers.Research purpose: The study aimed to develop a psychodynamic exposé of voluntary turnover by applying the conflict, identity, boundaries, authority, roles and task (CIBART) model to the lived experiences of high achievers.Motivation for the study: The research primarily focusses on voluntary turnover as an individual, rational decision-making process. It recognises the contribution of unconscious systems psychodynamics to voluntary turnover. Research conducted from this perspective is necessary to gain a more comprehensive and in-depth understanding of the topic.Research approach/design and method: Seven case studies of individual voluntary turnover were conducted in a large private retail company. Data were collected using free association narrative (FANI) interviews. The analysis of the data was guided by hermeneutic phenomenology, and the interpretive frame used was the CIBART model.Main findings: Six themes were constructed to describe the conflict dynamics along each of the six CIBART dimensions. Within each theme, the conflict dynamic is exposed, revealing the subsequent anxiety and defences that accumulate leading to the decision to leave. Ultimately, the six themes synthesise to propose that voluntary turnover is a conscious manifestation, yet an unconscious defence against system-wide conflict.Practical/managerial implications: Facilitating leaders’ understanding and processing of the conflict dynamics that occur across the CIBART dimensions, and which contribute to voluntary turnover, create opportunities for both transformation and prevention.Contribution/value-add: The research offers insights into the psychodynamics of voluntary turnover, which consulting psychologists and organisational leaders can utilise to address this phenomenon within their work groups.