Index

Citation (2023), "Index", Tyagi, P., Grima, S., Sood, K., Balamurugan, B., Özen, E. and Eleftherios, T. (Ed.) Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalised Economy (Contemporary Studies in Economic and Financial Analysis, Vol. 110B), Emerald Publishing Limited, Bingley, pp. 265-276. https://doi.org/10.1108/S1569-37592023000110B018 Publisher: Emerald Publishing Limited Copyright © 2023 Pallavi Tyagi, Simon Grima, Kiran Sood, B. Balamurugan, Ercan Özen, and Thalassinos Eleftherios INDEX Accounting, 146 Actual economic activity, 175 Administrative security controls in SME, current state of, 35–37 Africa, effect of COVID-19 debt accumulation, 165 Agriculture, 133 Alternative finance models, 102 Amazon (technology company), 98 Annual appraisals, 252 Anti-black Money Act (2015), 126 Anti-money laundering (AML), 60, 172 Apple (technology company), 98 Artificial intelligence (AI), 23, 85–86, 172, 217, 244, 252–253 ability of AI and SA to improve PM systems, 257 application of AI and SA in business processes, 255 automating PM Systems, 259–261 in business processes, 255–256 classification models to predict employee performance, 257–259 classification of AI, based on capabilities, 253–254 classification of AI, based on functionality, 254 competition, 219 demographics of customers, 219 drivers of digitisation and AI in retail, 218 in HR management, 259 limitations of AI and SA in PM systems, 261–262 for mapping cybersecurity controls for SME, 46–48 in PM systems, 257 retail customers, 218–219 retail digitisation using, 219–220 super, 254 technology and, 218 types, 253 Aspirational Districts Programme, The, 88 Asset management segment, 99 Augmented reality, 23 Authors’ network analysis, citation as per, 68–69 Autonomous robotics, 23 Balance sheet lending (BSL), 100 Bank 4.00, 102 Bank of Baroda, 7, 11–12 Bank of Hindustan, 2 Banking, 2, 98, 206 co-operative banks, 2 commercial banks, 2 industry, 205 payments banks, 2 small finance banks, 2 Banking, financial services, and insurance (BFSI), 29 Banking Regulation Act (1949), 2 Banks, 205 Bibexcel, 135 Bibliometrics, 57, 60 analysis, 141 of entrepreneurial universities, 57 R Package, 135 research, 141 Bibliometrix, 178 Biblioshiny, 178 Big data, 23, 85, 255 analytics, 84 BigTechs, 101 Billion Prices Project, 87 Black box model, 85 Black money, 58–59 Blending data sciences in economic and social issues, 86–87 Blockchain, 132 content analysis, 137–141 data analysis, 135–137 directions for future research, 141–142 implications, 141 methodology, 133–134 technology, 132 Bombay Stock Exchange (BSE), 75–76 Bootstrapping methods, 227 Bring your own device policy (BYOD policy), 40 Business domain-wise mission critical asset security (Business DMCAS), 43–44 Business to-Person lending models (B2P lending models), 101 Business-to-Business lending models (B2B lending models), 101 Businesses, 230 AI in, 255–256 changing priorities of CIA triad based on business domain, 30–31 SA in, 256–257 Buy Now Pay Later (BNPL), 101 C4.5 decision tree, 258 Canara Bank, 7, 9–10, 18 Capability maturity model (CMM), 26 Cashkumar (P2P lending platform), 107 version 2. 0, 108 Cashkumar Peer-to-Peer Lending Platform (Cashkumar P2P Lending Platform), 107–108 digital lending, 100–107 emotional analysis, 116–117 FinTech, 98–100, 108–109 literature review, 108 negative reviews, 119–120 P2P lending, 109–111 positive reviews, 118–119 research methodology, 112 sentiment analysis perspective, 111–112 theoretical background, 107 Castle approach, 28 Casual conversations, 250 Central Bank, 193 Central bank digital currency (CBDC), 190 Central Bank of Nigeria, 190 CIA triad assess priority of CIA triad for DMCA, 43 changing priorities of CIA triad based on business domain, 30–31 CIA trinity, 27 Citation network analysis, 67–68 citation as per authors’ network analysis, 68–69 Cloud computing, 23, 86 Co-authorship analysis, 60 Co-authorship network analysis as authors on money laundering, 62–66 as countries, 64–66 Co-occurrences analysis, 60 of keywords analysis on money laundering, 66–69 network analysis on money laundering, 66 Co-operative banks, 2, 4 Commercial banking, 2 Commercial banks, 2 foreign banks, 3 private sector banks, 3 public sector banks, 3 RRBs, 3 Communications service providers, 101 Companies Act, 105 Competitive pressure, 229 Conceptual model constructs and items measured, 221–223 development of, 221 Conceptual research model, 221 Confidence interval (CI), 227 Consumers, 216 Consumption of goods and services, 22 Content analysis, 137, 179 digitisation of agriculture, 140 supply chain management, 140 sustainable economic development, 140–141 Cooperative savings, 59 Cooperative Societies Act (1912), 4 Core cybersecurity concepts, 26–31 changing priorities of CIA triad based on business domain, 30–31 CIA Triad, 27 Defence in Depth, 28–29 DMCA, 29–30 Coronavirus, 162 Corporation threat agents, 24 Corruption, 56, 124 Cost-benefit analysis, 84 COVID 19, 5, 218 Africa, 165 effect of COVID-19 debt accumulation, 164 debt crisis, 164 debt statistics, 162–164 Europe, 164–165 global debt crisis, 161 heavily indebted countries, 167–168 and Indian Banking, 5 literature review, 161–162 methodology, 161 multilateral organisations, 166–167 pandemic, 160, 234–235 rich countries, 165–166 solution to overcome, 165 Cross industry standard process for data mining (CRISP-DM), 257 Crowdfunding, 99–100 Cryptocurrencies, 98 Customer relationship management (CRM), 253 Customers, 229 demographics of, 219 screening process, 58 Cutting-edge technology, 58 Cyber assets, 27 Cyber risk, 23 Cyberattacks faced by SMEs, experience of, 39–40 Cybercrime, 56 Cybercriminals, 37, 40 Cybersecurity, 23 calculate SME’s minimum overall cybersecurity controls implementation level, 44–45 implement prioritised cybersecurity controls for Business DMCAS, 43–44 responsible AI for mapping cybersecurity controls for SME, 46–48 Cybersecurity framework (CSF), 25 Cyberspace, 23 Data analysis, 224 measurement model, 224–226 structural model, 226–229 test, 224 tool, 88 Data collection, 223–224 Data extraction, 134 Data lags, 91–92 Data localisation problem, 92 Data mining, 85 techniques, 90 Data privacy and security, 91 Data science, 86 techniques, 85 Data-driven policy, India’s stance on, 87–89 Debt crisis, 161, 164 Debt restructuring, 162 Debt Service Suspension Initiative (DSSI), 166 Debt statistics, 162 external debt stocks, 162–163 massive spending by richer countries, 163–164 sovereign default, 164 Decision Tree, 257 Decision-making management, 173 Defence in depth (DiD), 28 Delay payments, 204 Democratisation of opinions, 236 Descriptive analysis, 60 Desktops, 40 Digital circuits, 22 Digital government, 87 Digital India campaigns, 89 Digital lending, 100 alternative finance models, 102 ecosystem, 100–102 functional business models in India, 105–107 funds transfer mechanism as per RBI guidelines, 105 global scenario, 101 governing enactments, 104–105 India, 102 landscape, 102–104 market share, 102 Digital sentiments, 236 Digital technologies, 109 Digital transformation, 216 in agriculture, 141 Digitalisation process of banking industry, 6 Digitisation intelligence competition, 219 demographics of customers, 219 drivers of digitisation and AI in retail, 218 retail customers, 218–219 technology and AI, 218 Digitisation of agriculture, 133, 140 Digitisation transforms retailing exchanges, 220 Directorate of Enforcement (ED), 126 Dirty money, 124 Document-term matrix (DTM), 178 Domain-wise Least Cybersecurity Implementation Framework (DLCI Framework), 41 assess priority of CIA triad for DMCA, 43 calculate SME’s DLCI Level, 45–46 calculate SME’s DMCAS Level, 44 calculate SME’s minimum overall cybersecurity controls implementation level, 44–45 identify DMCA, 41–43 implement prioritised cybersecurity controls for business DMCAS, 43–44 responsible AI for mapping cybersecurity controls for SME, 46–48 WCCI for SME, 44 Domain-wise Mission Critical Asset (DMCA), 29–30 Domestic lending by banks, 205 Drug trafficking, 56 e-CNY, 192 E-commerce platforms, 101 sites, 216 Earnings management, 146 conceptual framework, 147 income-targeting approach, 150–151 literature review, 148–150 priority theory of sustainable finance, 147–148 surplus income model, 152–155 surplus income model for sustainability, 151–152 Econometric models, 84 Economic and financial performance in topic modelling framework, relationship between money laundering and, 184–185 Economic growth (EG), 125, 128, 161, 173, 201 Electric vehicles infrastructure, investment target for, 202 Electronic word of mouth (e-WOM), 235 Embed quality assurance, 47 Emotion Lexicon (EmoLEX), 111 Emotional analysis, 116–117 Emotions, 116 Employees, 245, 258 in India, 175 narrow assessment of, 252 performance, 245 threat agents, 24 eNaira, 190, 193–195 CBDC, 190 money, 190 performs, 190 speed wallet, 196 Environmental, social and governance (ESG), 76, 79–81 ESG-based socially responsible investments, 75 Indian investors looking for, 75–76 Environmental accounting, 149 Environmental reporting, 146 Europe, effect of COVID-19 debt accumulation, 164–165 European Central Bank (ECB), 162 External debt stocks, 162–163 External incentives, 154 External stakeholders, 248 Facebook (technology company), 98 Federal Bank, 7, 13–14, 18 Finance models, 102 Financial Action Task Force (FATF), 58, 125 Financial crimes action plan for resolving financial crimes using SRI–ESG model, 81 channel for, 77–78 effects of, 79 terrorism financing devastating part of, 78–79 impact of unethical investments on, 79 Financial crisis (2008), 98 Financial industry, 205 Financial institutions, 205 in achieving sustainable economic goals, 206–207 through priority sector lending, 208–210 Financial markets, 101, 104 Financial performance Bank of Baroda, 11–12 Canara Bank, 9–10 co-operative banks, 4 COVID 19 and Indian Banking, 5 COVID 19, 5 data analysis, 8 data collection, 7 Federal Bank, 13–14 findings, 17–18 foreign banks, 3 HDFC Bank, 14–15 hypothesis testing for net profit, 16–17 hypothesis testing for NPA, 17 ICICI Bank, 12–13 Indian Bank, 10–11 limitation of study, 8 literature review, 5–7 non-performing assets, 4 non-scheduled banks, 4 payments banks, 4 private sector banks, 3 public sector banks, 3 research methodology, 7 research methodology, 8 research objectives, 7 RRB, 3 sample frame, 7 schedule banks, 4 small finance banks, 3–4 in topic modelling framework, relationship between money laundering and economic and, 184–185 Union Bank, 10 Yes Bank, 15–16 Financial services, 98 Financial study, 58 Financial Technology (FinTech), 98 branches of FinTech Industry, 99–100 classified into the following types, 98–99 credit, 102 landscape, 99 lenders, 101 start-ups, 109 Financing segment, 99 Firms, 147 Five-year planning process, 87 Forecasting methods, 84 Foreign Banks, 3 Formal process in PM systems, 249–250 Fugitive Economic Offenders Act (2018), 126 Functional business models in India, 105–107 Funds transfer mechanism as per RBI guidelines, 105 Global economy, 160 Global reporting initiative (GRI), 149 Globalisation of economies, 124 Gold medal, 238 Goods and Service Tax, 126 Google (Private companies), 91, 98 reviews, 114 Governance in India, 87 reporting, 146 Grameen Foundation, The, 87 Green accounting, 149 Green banking assessing funding needed by international agency, 205 investment target for electric vehicles infrastructure, 202 investment target for renewable energy generation, 201–202 investment target to set up smart cities, 203–204 methodology, 206 results, 206 role of financial institutions in achieving sustainable economic goals, 206–207 role of financial institutions through priority sector lending, 208–210 Green development, 210 Green energy, 210 Green growth, 206 Gross domestic product (GDP), 160, 174, 205 HDFC Bank, 7, 14–15, 18 Human bias, 252 Human resources (HR), 172, 255 AI in HR management, 259 Human-based PM systems, 252 Hume’s Aesthetic Theory, 108 Hypothesis testing for net profit, 16–17 for NPA, 17 ICICI Bank, 7, 12–13, 18 ID3 decision tree, 258 Illicit drug trafficking, 59 IMF Fact Sheet, 125 Income smoothing, 151 Income-targeting approach, 150–151 Incremental approach, 84 India current market trend of, 74–75 digital lending, 102 functional business models in, 105–107 measurements to control money laundering terror funding in, 125–126 retail scenario in, 217–218 SRI in, 75 stance on data-driven policy, 87–89 Indian Bank, 7, 10–11 Indian banking industry, 4 sector, 2 Indian Economy future implication of study, 128 impacts of money laundering on, 126–127 impacts of terror financing on, 127–128 measurements to control money laundering terror funding in India, 125–126 nexus of money laundering and terrorism financing, 125 Indian government, 90 Indian investors looking for ESG Investments, 75–76 Industry 1.0, 22 Industry 2.0, 22 Industry 4.0 digitisation, 23 Inferential research approach, 223 Informal economy, 174 Informal process in PM systems, 250 Information and communications technologies (ICTs), 23, 88, 217 assets, 27 Information security, 27 Information security management system (ISMS), 24 Information technology, 124 Institute for Energy Economics and Financial Analysis (IEEFA), 201 Insurance, 98 Intangible assets, 27 Integration of economies, 124 Interest-bearing eNaira, 194–195 Internal stakeholders, 248 International agency, assessing funding needed by, 205 International Energy Agency (IEA), 205 International Monetary Fund (IMF), 163, 175 International Standards Organization, 260 Internet of Things (IoT), 23, 84, 86, 255 Investment, 98 management, 175 target for electric vehicles infrastructure, 202 target for renewable energy generation, 201–202 target to set up smart cities, 203–204 IP Act (2000), 91 Keynesian model, 193 Know Your Customer (KYC), 106 Knowledge management cybersecurity, 40 Laptops, 40 Latent Dirichlet allocation (LDA), 179 Lender’s Club, 110 Lending policies, 205 Lending practices, 206 Link strength, 137 Logical controls, 35 Machine learning (ML), 86, 257 Malware assaults, 39 Management accounting, 148 Managerial discretion, 147 Managers and employees, 245–246 Market share, 102 Marketers, 218 Marketplace lending (MPL), 100 Massive data analysis approach, 59 Measurement model of data analysis, 224–226 Medal, 238 Mendeley database, 133 Mentor–Protege relationship, 250 Micro, small and medium enterprises (MSMEs), 208 Microsoft (Private companies), 91 Minerals, 30 Mission critical assets, 29 MIT Sloan School of Management, 87 Modern banking, 2 Money, 56 Money laundering, 60, 79, 124, 172–173 analysis of word cloud, 181 annual trend of publication, 61 citation network analysis, 67–69 co-authorship network analysis, 62 co-authorship network analysis as authors on, 62 co-authorship network analysis as countries, 64–66 co-occurrences network analysis on, 66–67 countries analysis, 62 data and methodology, 175–179 descriptive analysis, 179–180 historical background of, 58–60 impacts of money laundering on Indian economy, 126–127 investigating TF-IDF, 182–184 link between words, 181 literature review, 173–175 measurements to control money laundering terror funding in India, 125–126 nexus of, 125 relationship between money laundering and economic and financial performance in topic modelling framework, 184–185 research methodology and data, 60 results, 61 sources analysis, 61–62 Money lending, old concept of, 100 Mordor Intelligence, 89 Naïve Bayes classifiers, 258 Narcotic Drugs and Psychotropic Substances Act (NDPS), 59 NASSCOM, 89 National Association of Securities Dealer Automated Quotations, The, 98 National Strategy for Artificial Intelligence by NITI Aayog, 88 Natural catastrophes, 24, 34 Natural disasters, 34 Neo banks, 101 Net profit, hypothesis testing for, 16–17 Netnograhphy, 236 Nigeria CBDC, 190 current features of, 193–194 interest-bearing eNaira, 194–195 literature review, 191–193 no transaction costs, 195 redesigning, 194 security, 195–196 NIRAMAI, 88 NIST, 25 NITI Aayog, 88 Non-banking financial corporations (NBFCs), 100, 206 Non-performing Assets, 4 Non-performing loans (NPL), 162 Non-scheduled banks, 2, 4 Normalisation, 178 NPA, hypothesis testing for, 17 Offline P2P lending, 100 Olympic Games Tokyo (2020), 237 Olympics, 240 destination, 234 players, 239 Online P2P lending platforms, 100, 109–110 Online platforms, 40 Opaque system, 252 Open Government Data (OGD), 87 Opensource Stack software, 87 Oracle (Private companies), 91 Organisation-owned devices, 40 Organisational goals, 246 Organisations, 244 Organised retailers, 230 Organised retailing, 221, 223 Palantir Technologies (American software company), 87 Pandemic, 160 Parallel economy, 124 Partial least square (PLS), 224 Payment, 191 Payments Banks, 2, 4 Performance appraisal (PA), 244 Performance assessments, 249 Performance improvement, notifications of, 249–250 Performance management systems, 244–245 AI and SA, 252–257 AI and SA in PM systems, 257–262 components of, 245–246 formal processes, 249–250 informal processes, 250 inputs to PM systems, 250–251 issues in current PM systems, 251–252 monitoring, 246–247 outputs from PM systems, 251 planning, 246 principles of PM systems, 248–249 processes in PM systems, 249 reviewing, 247 rewarding, 247 stakeholders in PM systems, 247–248 tasks in PM Systems, 246 Person-to-Business lending models (P2B lending models), 101 Person-to-Person lending models (P2P lending models), 101, 109–111 crediting, 109 elements, 100 lending platforms, 100–101, 106 lending services, 104 Physical retailers, 216 Physical security current state of physical security controls in SME, 34 measures, 34 Physical stores, 217 Planning–programming–budgeting system, 84 Platform lending, 100 Policy-making process, 84 in India, 87 Predictive modelling techniques, 85 Prevention of Money Laundering Act (PMLA), 59, 126 Priority sector lending role of financial institutions through, 208–210 Priority theory of sustainable finance, 147–148 PRISMA 2020 Flow Diagram, 133 Private Banks, 8, 18 Private companies, 91 Private giants, 89 Private Sector Banks, 3 Production-linked Incentive Scheme (PLI Scheme), 207 Profitability, 5 of Indian banks, 7 Programmable integrated circuits (PLCs), 22 Public policies, 84 Public Sector Banks, 3, 8, 18 Python application, 112, 114 Qualitative research techniques, 85 Quality assessment, 134 Quasi-legal enterprises, 56 Real-time resource monitoring techniques, 85 Refugee Olympic, 237 Regional Rural Banks (RRB), 2–3 Relative frequency, 183 Renewable energy, 22, 201, 207 investment target for renewable energy generation, 201–202 Research methodology, 85 Reserve Bank of India (RBI), 2, 6, 99, 207 funds transfer mechanism as per RBI guidelines, 105 Reserve Bank of India Act (1934), 2, 4 Resource allocation, 76 Retail business analytics, 219 Retail customers, 218–219 Retail digital promotion, 220–221 Retail industry, 221 Retail scenario in India, 217–218 Retail stores, 216 Retailers, 216–217, 229 Retailing, 220 data analysis, 224–229 data collection, 223–224 development of conceptual model, 221–223 drivers of digitisation and AI in retail, 218–219 implications of study, 229–230 limitation, scope for further research, 230 literature review and hypothesis development, 217 research methodology, 223–223 research objectives, 217 retail digital promotion, 220–221 retail digitisation using AI, 219–220 retail scenario in India, 217–218 Reward system, 247 Rio Olympic (2016), 236 Scalability, 252 Schedule Banks, 4 Scheduled banks, 2 Search strategy, 133 Security awareness training for employees in SMEs, frequency of, 37–38 Security controls in SME, current state of, 34 Security objectives, 27, 29 Selection criterion, 133–134 Sentiment analysis, 238 method, 114 perspective, 111–112 Sentiments, 236 Sin stocks, 80 Small and Medium Enterprises (SME), 22, 31 age of, 32 analysis of research interview results, 41 analysis of research survey results, 32 biggest problems faced by SMEs implementing or deciding/planning to implement cybersecurity controls, 38–39 core cybersecurity concepts, 26–31 current state of administrative security controls in, 35–37 current state of implemented standards or framework in, 32–33 current state of physical security controls in, 34–35 current state of security controls in, 34 current state of technical security controls in, 35 DLCI framework, 41–48 DLCI Level, 45–46 DMCAS Level, 44 experience of cyberattacks faced by, 39–40 frequency of security awareness training for employees in, 37–38 literature review, 24–26 methodology, 31–32 minimum overall cybersecurity controls implementation level, calculate, 44–45 responsible AI for mapping cybersecurity controls for, 46–48 WCCI for, 44 Small and medium-sized businesses (SMBs), 23, 101 Small business owners, 109 Small finance banks, 2–4 Smart Analytics, 252, 254–255 ability of AI and SA to improve PM systems, 257 AI in HR management, 259 application of AI and SA in business processes, 255 automating PM Systems, 259–261 benefits of, 255 classification models to predict employee performance, 257–259 limitations of AI and SA in PM systems, 261–262 in PM systems, 257 SA in business processes, 256–257 Smart cities, investment target to set up, 203–204 Social accounting, 148 Social media, 219, 235 Social reporting, 146 Socially responsible investments (SRI), 74–76, 79–81 action plan for resolving financial crimes using SRI–ESG Model, 81 current market trend of SRI in India, 74–75 effects of financial crimes, 79 ESG and SRI, 79–81 findings of study, 77 heterogeneity, 76 in India, 75 investors, limitations of study, 77 research 77 research methodology, 77 review of socially responsible 75–76 76 terrorism financing devastating part of financial 78–79 impact of unethical investments on financial crimes, 79 unethical investors, 77–78 41 energy generation, 201 234 234 239 239 149 in PM Systems, 247–248 107 Bank of India 2 Data Analysis, 224 theory 235 modelling 224 model of data analysis, 226–229 178 chain management, 140 income model, implication of model, implications for or for sustainability, 151–152 profit, 206 149 Sustainable development, 206 Sustainable development Sustainable economic development, 140–141 Sustainable economic goals, role of financial institutions in 206–207 Sustainable 147 Sustainable growth in India, 206 security 26 18 249 (Private 89 98 controls, 35 security controls in SME, current state of, 35 132 and AI, 221 companies, 98 Technology and and model Technology governance data sciences in economic and social issues, 86–87 India’s stance on data-driven policy, 87–89 research and methodology, findings and 22 frequency 179 investigating TF-IDF, 182–184 financing on Indian economy, impacts of, 127–128 59 financing, 79 devastating part of financial 78–79 nexus of, 125 threat agents, 24 analysis, 178 data methods, 178 agents, 24 Tokyo Olympic (2020), 234 data analysis and findings, literature review, research methodology, 236 Tokyo Olympic 234 179 relationship between money laundering and economic and financial performance in, 184–185 profit, action 236 PM systems, 252 149 253 234 content analysis, 236 data, 236 sentiments, 235 laundering system, 59 investments on financial crimes, impact of, 79 investors, 77–78 payments 6 Union Bank, 7, 10 56 National Security 28 224 analysis, 60 60, 135 23 87 40 of 173 Cybersecurity Implementation 44 22 23 Yes Bank, 7, 18 25 COVID 19 and Financial Performance of Banks in and of Least Cybersecurity for Small and Medium Enterprises for Global Digitalised Economy Money of from to Socially for Financial Technology and of Governance and Policy-making for the the Sentiment Analysis of Cashkumar Peer-to-Peer Lending on Google of Money Laundering and Financing on the Indian Economy the on Implementation of in Earnings Management for Income of Sustainable COVID-19 Global Debt to the Analysis of Money Laundering Research the Central Bank Digital for Payments and Green Banking to Sustainable Economic Digitisation and Artificial Intelligence in Sector on Sentiment Analysis in 2020 Smart and AI for Modern Performance Management

Digital development for a progressive networked society

Global E-waste management: Can WEEE make a difference? A review of e-waste trends, legislation, contemporary issues and future challenges

Providing security to bank customers is the prime responsibility of banking institutions. These institutions upgrade their services to provide convenience-based banking exposure. Automatic Teller Machines (ATMs) assist the bank's customers to operate independently. ATMs verify the authenticity of the user through a 4-digit personal identification number (PIN) only. The State Bank of India (SBI) has initiated a double security check system to minimize the probabilities of banking frauds through ATMs. SBI customers must provide a one-time password (OTP) along with a PIN to complete the cash withdrawal transaction through the SBI ATM. The objective of the study is to analyze the impact of financial security enhancement in ATMs cash transactions through one-time password on the probabilities of banking frauds through ATMs. The study has used primary data collected through a questionnaire from 422 respondents. The study resulted that one-time password has enhanced the financial security function of ATMs and now the probabilities of ATM frauds has been reduced substantially.

The Urgency of This research is that SMEs in Indonesia face limited access to capital show a solution to overcome the problem of funding sources to finance SMEs by proposing financing models through crowdsourcing or crowdfunding mechanisms.The crowdfunding model in this study is lending (peer-to-peer) using profit-sharing principles such as mudharabah, which has not been widely studied.The purpose is to analyze whether increasing SME financial inclusion through crowdfunding based on profit-sharing principles is the right model for improving the financial aspects of SMEs in Indonesia and through the ERRC (Blue Ocean Strategy) approach Which factors must be eliminated (Eliminate), reduced (Reduce), improved (Raise) and created (ERRC) The research objective also analysis of the model of increasing SME financial inclusion through Profit-sharing principle-based crowdfunding with a Business Model Canvas approach.Research Methodology: Establishing Key Success Factor, ERRC eliminated (Eliminate), reduced (Reduce), improved (Raise) and created (ERRC), Canvas Strategy conducted on 12 informants from SMEs in 6 cities Surabaya, Batu, Malang, Pasuruan, Sidoarjo and Gresik to develop Blue Ocean strategyThe results of this study are In Indonesia, small and medium enterprises (SMEs) are one of the most important industries in the economy.This study analyzes whether increasing SME financial inclusion through crowdfunding based on profit-sharing principles is the right model for improving the financial aspects of SMEs in Indonesia.This research uses source triangulation research using data in the form of documentation, observation and interviews with several informants who are considered to have different points of view and meet the criteria for the study.It is expected through the ERRC (Blue Ocean Strategy) approach that factors must be eliminated (Eliminate), reduced (Reduce), improved (Raise) and created (ERRC) as well as the Business Model Canvas Approach to establish a model of Crowdfunding SME, namely, aspects of attraction, amenities, accessibility, environmental sustainability, community empowerment, marketing and industrial aspects.The results of this study show that stakeholders expect a rebranding by eliminating environmental sustainability aspects, lowering attraction aspects, raising accessibility and empowerment aspects, and creating industry aspects while creating value-cost trade-offs with a focus on two aspects of the tourism industry: adjusting the pattern of cooperation and community development.

PurposeThis study investigates the psychological adoption of technology in relation to employees' mental beliefs about using technology in their workplace, because it is necessary to investigate the direct and indirect effects of information systems (IS) on employees' work-related results that underpin creativity and engagement.Design/methodology/approachUsing a cross-sectional design, data were collected from 153 human resource (HR) employees who used human resource information systems (HRIS) in small- and medium-sized enterprises (SMEs) in Malaysia.FindingsThe results show that effective acceptance and adoption of an HRIS enables HR employees and management in SMEs to be creative, balanced and engaged. Facilitating conditions and task-technology fit positively affect the behavioral intention to accept and adopt an HRIS. Additionally, organizational citizenship behavior moderates the relationship between the behavioral intention to accept and adopt an HRIS and employee creativity.Originality/valueThis study significantly advances the fields of human resource management and IS by elucidating the factors influencing employees' adoption of technology. In an effort to address a research gap in existing research, it introduces a unified theory of acceptance and use of technology, which precedes the psychological adoption process by individuals. Furthermore, it offers both empirical and theoretical insights into the interplay between technology adoption factors and their subsequent impact on work-related outcomes.

In the recent years significantly increased interest in the recovery of non-ferrous metal from waste of electrical and electronic equipment (WEEE) has been observed. This waste is classified as hazardous waste because it contains both toxic metals such as lead or mercury and organic components such as polychlorinated biphenyls. For these reasons disposing of this waste is understandable. In Poland many companies have been founded that are involved in recycling of WEEE waste. Typically, companies operating in this sector are one of the Small and Medium Enterprises (SMEs). The overriding objective of the SME sector recycling is to increase the degree of exploitation of metallic waste in an economically justifiable way. This paper focuses on some of the above-mentioned issues of technological and qualitative assessment of risks associated with recycling of metal, in principle copper, from WEEE. There are several examples given of the risks faced by domestic companies in the SME recycling WEEE sector.

In today’s uncertain business environment, Micro, Small, and Medium Enterprises (MSMEs) play a vital role in economic growth, especially in developing countries like the Philippines. However, their limited access to management tools and resources makes them vulnerable to risks. This study examined the relationship between risk management practices and MSME competency, guided by the COSO Enterprise Risk Management (ERM) Framework (2013). It aimed to: (1) analyze MSME profiles (income, sector, assets, employees, years of operation); (2) assess the usage and effectiveness of risk management practices; (3) identify differences and relationships across business profiles; and (4) propose a practical risk management action plan. Findings showed that most MSMEs earn Php 9,000–35,000 monthly, have assets below Php 3 million, employ fewer than 10 workers, and operate mainly in wholesale/retail trade. Despite resource constraints, risk management—particularly in compliance, financial, and strategic areas—was rated “highly effective.” Significant differences emerged by income, assets, and years in operation, while correlation analysis revealed a strong positive link (r = 0.6102) between risk management effectiveness and overall competency. The study proposed a development plan including seminars on sustainable risk strategies, simplified loan processes, and digital promotion tools to strengthen MSME resilience and long-term sustainability. The research supports the UN Sustainable Development Goals (SDGs): SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities), and SDG 17 (Partnerships). Overall, it highlights the transformative role of integrated risk management in enhancing MSME performance, resilience, and competitiveness.

PurposeThe purpose of this paper is to examine the driving forces, challenges benefits, barriers and strategies to decrease barriers to information and communication technologies (ICTs) adoption and assimilation by small‐ and medium‐sized enterprises (SMEs) in this era of globalization.Design/methodology/approachThe paper is based on a review of literature, both online and print.FindingsThe paper concludes that, ICTs adoption and assimilation in SMEs is critical to enhance their competitiveness. In addition, ICTs usage in SMEs will enhance accessibility into the international markets.Research limitations/implicationsThe major limitation of this paper is that it only reviews relevant literature and that empirical findings are not obtained to give an insight and holistic view of ICTs adoption and assimilation by SMEs.Practical implicationsEffective use of ICTs in SMEs has great impact on its competitiveness and sustainability. In addition, owners/owner managers, policy makers and other stakeholders would be in a position to understand the challenges faced by SMEs in ICTs adoption and come up with various interventions to assist SMEs.Originality/valueDespite the challenges faced by SMEs on ICTs adoption, SMEs stand to benefit from adopting ICTs in their business processes especially in accessing international markets. SMEs play a great role in the economy and thus need special attention.

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in economic development, employment generation, and sustainable growth. However, their adoption of Sustainable Development Goals (SDGs) faces several financial, technological, regulatory, and market-related challenges. This study aims to identify and analyze the major barriers faced by MSMEs in achieving SDGs. A structured questionnaire was administered to 120 MSME respondents in Haryana, capturing perceptions on 15 key sustainability challenges. Data were analyzed using descriptive statistics and one-way ANOVA to examine variations in perceptions across age demographics. Results indicate that financial constraints, high cost of green technologies, lack of technical knowledge, and limited awareness of SDGs are perceived as the most critical challenges. ANOVA results reveal that age does not significantly influence the perception of these challenges, suggesting that barriers are systemic rather than age-dependent. The findings highlight the need for policy interventions, financial support, capacity building, and market incentives to facilitate SDG adoption among MSMEs. The study contributes to the literature by providing empirical evidence on the challenges of sustainable practices in MSMEs and offers practical implications for policymakers and business support agencies.

The Sustainable Development of ICTs in China: An Empirical Study of Small and Medium-Sized Enterprises

Due to a shortage of funding and other market challenges, Small and Medium-sized Enterprises (SMEs) face difficulties in adopting new technologies. Numerous technological obstacles negatively impact the long-term commercial achievement of SMEs. The deployment of Industry 4.0hopes to resolve these technological challenges. A sustainable city is a complex structure where economic, societal, and ecological components interact and compete. There is a scarcity of l methodologies for measuring interactions in this complex structure. Industry 4.0 aims to obtain higher performance effectiveness, profitability, and automation. The main goal is to develop a reliable method of evaluating small and medium-sized enterprises (SMEs) adopting Industry 4.0 technologies, particularly concerning smart city applications. This paper aims to determine the influence of Industry 4.0 in fostering economic efficiency and sustainability amongst these SMEs. The study introduces a multi-criteria decision-making (SC-MCDM) system designed to test an SME’s achievement of their targeted sustainable developmental goals. A technique for computing the interaction between various standards, i.e., (static interactions and dynamical pattern resemblance), as well as the weightage of variables of every indicator generated by the connection, is included within SC-MCDM. Furthermore, applying the suggested technique is validated by assessing the sustainable development goals of twelve Chinese cities within the Triple Bottom Line (TBL) paradigm. From a geographic-temporal viewpoint, spatial variations in city sustainability reveal regional sustainable inequalities. Indicator scores suggest that the most significant factors for most communities are the lack of research spending, falling financing in stationary assets, shortage of financial development, and inadequate shared transit. Furthermore, the growth of tertiary industries, improvement of energy performance, expansion of green areas, and reduction of pollution emissions are key driving forces for enhancing sustainability. Compared to other methodologies, Multi-Criteria Decision Making (MCDM) considers the interplay between conditions. This is why it is an excellent approach to assess the sustainability of any city. Our experimental findings highlight the impact of MCDM and sustainability towards achieving a city’s sustainable development goals. Compared to other methods, the SC-MCDM system is more successful rate of 89.7%, a more sustainable rate of 92.1%, a more precise ratio 93%), more accurate (95%), and a less mean absolute error, and mean squared error rate of 8.3% while trying to achieve sustainable city development goals. Doi: 10.28991/HIJ-2024-05-04-018 Full Text: PDF

To succeed, SMEs must create legitimacy by mimicking the cues that signal credibility to convince potential stakeholders that something stands behind their promises. This research examines the role of information and communications technology (ICT) in legitimacy-building from the perspective of both SME founders and potential customers. Small and medium-sized enterprises (SMEs) face more serious challenges to their survival than do larger firms. To succeed, SMEs must establish and maintain credibility in the marketplace to attract the resources required for survival. Most borrow legitimacy by mimicking the cues that signal credibility to convince potential stakeholders that something stands behind their promises. This research examines the role of information and communications technology (ICT) in legitimacy creation from the perspective of both SME founders and customers. In-depth, semi-structured interviews were conducted in a variety of industries to determine whether the ICT-related legitimacy schema from the customers’ perspective differs substantially from that of firm founders. Results indicate that customers compare the ICT information provided in SME’s sales pitches to pre-existing ICT expectations about the nature of desirable sales transactions. We describe the relationship between violations of ICT expectations, legitimacy, and purchase decisions. Implications for theory and practice are discussed.

Information and Communication Technologies (ICTs) have become an integral part of today’s economy. Small and Medium-sized Enterprises (SMEs) have been increasingly enjoying the benefits of e-business. ICT introduces both opportunities and threats to the SME. The general consensus of opinion is that SMEs that have traditionally been restrained from international trade because of resource limitations are now able to present themselves and their products globally.Despite these benefits, the uptake of e-business by SMEs is still low. There are still many issues that should be addressed before SMEs can be convinced to embrace ICT. For SMEs to remain competitive in a rapidly changing world, they need to take up the adoption of new technologies. This paper attempts to discuss the issues, ideas and innovations that are important to help SMEs to remain competitive.

Traditionally, it is believed that small- and medium-sized enterprises (SMEs) do not have enough ability to adopt and persistently practice social sustainability. This is because SMEs are not capital-intensive companies and neither are their returns nor skills. At the same time, the wellbeing of the employees in SMEs cannot be ensured and sustainable development goals cannot be achieved without making SMEs socially sustainable, as they account for the majority of world businesses. Moreover, the expectation of the stakeholders and subsequent pressure on SMEs to practicing social sustainability remains. Such pressure from the stakeholders creates a “mismatch problem” between stakeholders’ expectations and SMEs’ abilities to adopt socially sustainable practices. This study aims to explore what factors are responsible for this “mismatch problem”, and how SMEs can handle this mismatch to be socially sustainable firms. Based on a rigorous literature review, this study reveals that both internal issues, such as a lack of resources and awareness, and external issues, such as the non-existence of a tailored social sustainability standard for SMEs and lack of institutional support, are responsible for this gap. This study develops several propositions that highlight the requirements in various situations and provides strategies outlining the implications for SMEs and their stakeholders to make SMEs socially sustainable. Overall, this study discloses that cooperative support from stakeholders, especially during a disruption such as the COVID-19 pandemic, a finance mechanism, the development of awareness and human capital in SMEs, and a unified standard for SMEs are likely to improve social sustainability practices in SMEs.