Template-Type: ReDIF-Article 1.0 Author-Name: Razib Chandra Chanda Author-X-Name-First: Razib Chandra Author-X-Name-Last: Chanda Author-Name: Ali Vafaei-Zadeh Author-X-Name-First: Ali Author-X-Name-Last: Vafaei-Zadeh Author-Name: Syafrizal Syafrizal Author-X-Name-First: Syafrizal Author-X-Name-Last: Syafrizal Author-Name: Haniruzila Hanifah Author-X-Name-First: Haniruzila Author-X-Name-Last: Hanifah Author-Name: Karpal Singh Dara Singh Author-X-Name-First: Karpal Singh Dara Author-X-Name-Last: Singh Title: Investigating the determinants of mobile shopping applications continuance usage intention in the post-COVID-19 pandemic Abstract: As COVID-19 evolves and weaken overtime, countries have begun to relax lockdowns, mobility restrictions, and allow businesses and societies to return to normal. Therefore, this study aims to investigate determinants of continuance intention to use mobile applications in the post-pandemic era. Based on the expectation-confirmation theory, the study obtained data from 375 respondents through a quantitative research strategy. The findings of this study show that expectation-confirmation influences satisfaction. Perceived usefulness had a positive influence on both satisfaction and continuance intention to use mobile applications. Customer satisfaction was also found to positively influence continuance intention to use mobile applications. Notably, the study also found that perceived privacy risk negatively moderates the relationship between satisfaction and continuance intention. The study contributes to the continuance intention literature and highlights important factors that can influence customers to continue using mobile applications in the post-pandemic era. Journal: Int. J. of Applied Management Science Pages: 326-351 Issue: 4 Volume: 15 Year: 2023 Keywords: mobile shopping applications; continue use intention; satisfaction; confirmation; perceived privacy risk; perceived usefulness. File-URL: http://www.inderscience.com/link.php?id=134426 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:4:p:326-351 Template-Type: ReDIF-Article 1.0 Author-Name: Clóvis Santos Author-X-Name-First: Clóvis Author-X-Name-Last: Santos Author-Name: Carina Dorneles Author-X-Name-First: Carina Author-X-Name-Last: Dorneles Title: Global schema as local data integrator using active learning to identify candidates attributes Abstract: Data integration represents a challenge in application development. Although there are several alternatives to data integration, such as federated and distributed databases, there are still problems with the standardisation of distinct data sources, and this happens because different companies develop distinct systems with different paradigms and concepts. In this paper, we present a case study, in the agriculture and environment domain, of an essential point in the data integration domain which is to show resources to identify nearby attributes concerning the characteristics of the content foreseen in the requirements presented in the proposed schema. Information technology experts in agribusiness help map the most relevant attributes for the investigated scenario. In our experimental tests, we used a quantitative method data analysis approach to validate the results with quantitative comparisons regarding the percentages of proximity between the attribute contents in the databases. Our proposal presents an alternative to simplify data integration without intermediate application or middleware layers. The results were measured on a scale between 0% and 100% to identify candidate attributes. The results were good in identifying attributes in the databases in almost 67% of the cases. Journal: Int. J. of Applied Management Science Pages: 296-310 Issue: 4 Volume: 15 Year: 2023 Keywords: agribusiness; database; text mining; data extraction; machine learning. File-URL: http://www.inderscience.com/link.php?id=134427 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:4:p:296-310 Template-Type: ReDIF-Article 1.0 Author-Name: Gaurav Nagpal Author-X-Name-First: Gaurav Author-X-Name-Last: Nagpal Author-Name: Udayan Chanda Author-X-Name-First: Udayan Author-X-Name-Last: Chanda Title: P-Model of inventory optimisation for high technology multi-generation products under limited warehouse storage space Abstract: This research work puts forward the inventory optimisation model for the high technology multi-generation products under the situation of limited warehouse storage space. It is assumed that the manufacturer has its own space which has a lesser opportunity cost of usage as compared to another rented space. Therefore, the manufacturer utilises the own storage space for the period of time where his own space is sufficient to keep the inventories. While the research work has been done earlier on various demand patterns under such a scenario, there is no research present under storage space constraints for the generations of innovative products whose demand follows the Norton Bass Model of Innovation Diffusion. This paper lays down such a model for inventory optimisation, but also puts forward a few theorems on the dynamics of inventory decisions, and also performs numerical illustrations of the proposed model. Journal: Int. J. of Applied Management Science Pages: 216-237 Issue: 3 Volume: 15 Year: 2023 Keywords: optimal inventory replenishment; storage space constraints; innovation diffusion; technology generations. File-URL: http://www.inderscience.com/link.php?id=133669 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:3:p:216-237 Template-Type: ReDIF-Article 1.0 Author-Name: Vishal Soodan Author-X-Name-First: Vishal Author-X-Name-Last: Soodan Author-Name: Shantanu Saha Author-X-Name-First: Shantanu Author-X-Name-Last: Saha Title: Applying an extended theory of planned behaviour to predict Indian customer's e-vehicle purchase intention Abstract: The purpose of this paper is to predict the intentions towards purchase of EVs in India This study has taken Theory of Planned Behaviour (TPB) as base and underlined its constructs to gauge the intentions by adding variables namely Environmental Concern and Openness to Experience. The data was collected on a structured questionnaire using systematic sampling. Total 443 filtered and sorted responses were taken into consideration for analysis out of total 988 questionnaires distributed in Ludhiana and Chandigarh cities of India. It was found that two components of TPB model, Attitude and Subjective Norms along with modified constructs: Environmental Concern and Openness to Experience, significantly explain intention towards EV purchase. However, Perceived Behavioural Control (PBC) was found to be insignificant. The study results will be helpful to policy makers and marketers in enhancing the understanding about decision making of customers to purchase an e-vehicle in India. Journal: Int. J. of Applied Management Science Pages: 258-276 Issue: 3 Volume: 15 Year: 2023 Keywords: commuting; environmental concern; personality; purchase intention. File-URL: http://www.inderscience.com/link.php?id=133670 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:3:p:258-276 Template-Type: ReDIF-Article 1.0 Author-Name: Indrani Maiti Author-X-Name-First: Indrani Author-X-Name-Last: Maiti Author-Name: Tarni Mandal Author-X-Name-First: Tarni Author-X-Name-Last: Mandal Author-Name: Surapati Pramanik Author-X-Name-First: Surapati Author-X-Name-Last: Pramanik Title: A goal programming strategy for bi-level decentralised multi-objective linear programming problem with neutrosophic numbers Abstract: This paper develops a goal programming (GP) algorithm to evaluate bi-level decentralised multi-objective linear programming problem (BLDMOLPP) in neutrosophic number (NN) environment. In a BLDMOLPP, a single decision maker (DM) is present at the upper level and multiple decision makers at the lower level. Here the parameters of the problem are considered to be NNs in the form of [<em>P</em>+<em>QI</em>], where <em>P</em> and <em>Q</em> are real numbers and indeterminacy is represented through the symbol <em>I</em>. <em>I</em> is expressed in the form of a real interval as agreed upon by the DMs. The BLDMOLPP with NNs then gets converted into an interval BLDMOLPP. Using interval programming, the target intervals for the objective functions are identified and subsequently, the goal achievement functions are constructed. The upper level DM provides some possible relaxation on the decision variables under his/her control to cooperate with the lower level DMs to attain a compromise optimal solution. Thereafter, goal programming (GP) models are formulated by minimising the deviational variables and thereby obtaining the most satisfactory solution for all DMs. Finally, a numerical example demonstrates the feasibility and simplicity of the proposed strategy. Journal: Int. J. of Applied Management Science Pages: 57-72 Issue: 1 Volume: 15 Year: 2023 Keywords: neutrosophic number; bilevel decentralised programming; multi-objective programming; goal programming. File-URL: http://www.inderscience.com/link.php?id=128294 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:1:p:57-72 Template-Type: ReDIF-Article 1.0 Author-Name: Fedia Daami Remadi Author-X-Name-First: Fedia Daami Author-X-Name-Last: Remadi Author-Name: Hela Moalla Frikha Author-X-Name-First: Hela Moalla Author-X-Name-Last: Frikha Title: The multi-criteria group decision-making FlowSort method using the output aggregation Abstract: Real-life problems are multifaceted in nature and can create ambiguity in decision-making. Consequently, it is difficult to make the scoring criteria precise and to ultimate the exact values of attributes in multi-criteria analysis. Usually, an individual DM cannot make a judgement alone. In fact, he was unable to effectively define the opinions and the favourites of the entire team using multiple criteria, as everyone seeks to demonstrate their personal impact on the process in terms of his individual and team interests. This paper examines one of the sorting methods, named FlowSort, and extends it to multi-criteria group decision-making based on the aggregation of individual sorting result outputs. The evaluation of each alternative is described by lexical terms that can be represented by triangular intuitionistic fuzzy numbers. To validate our extension, an illustrative example and empirical comparison with other multi-criteria decision-making methods is carried out. Journal: Int. J. of Applied Management Science Pages: 277-295 Issue: 4 Volume: 15 Year: 2023 Keywords: multi-criteria group decision-making; MCGDM; sorting problematic; intuitionistic fuzzy set; IFS; FlowSort method. File-URL: http://www.inderscience.com/link.php?id=134440 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:4:p:277-295 Template-Type: ReDIF-Article 1.0 Author-Name: Andrejs Čirjevskis Author-X-Name-First: Andrejs Author-X-Name-Last: Čirjevskis Title: Measuring dynamic capabilities-based synergies using real options in M%A deals: Amazon's acquisition of Whole Foods Abstract: Dynamic capabilities have become well established as a new imperative for organising M%A processes. However, understanding the full benefits and possible limits of real options applications to measure a dynamic capability-based (managerial) synergies remains a challenge. The author developed three propositions and justified them by application of dynamic capabilities framework and real options theory to highly strategic and not standard M%A deal: Amazon's acquisition of Whole Foods in 2017. The illustrative case study made it possible to bridge together two streams of research on dynamic capabilities and real options. While the empirical application of the dynamic capabilities' framework makes them more visible, the application of the real options is making dynamic capabilities measurable in the M%A deals. In the end, the author discusses theoretical and managerial contributions, limitations, and future work. Journal: Int. J. of Applied Management Science Pages: 73-85 Issue: 1 Volume: 15 Year: 2023 Keywords: merger and acquisition; dynamic capabilities; synergy; real option. File-URL: http://www.inderscience.com/link.php?id=128296 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:1:p:73-85 Template-Type: ReDIF-Article 1.0 Author-Name: S.K. Yadav Author-X-Name-First: S.K. Author-X-Name-Last: Yadav Author-Name: Dinesh K. Sharma Author-X-Name-First: Dinesh K. Author-X-Name-Last: Sharma Author-Name: Hari Sharma Author-X-Name-First: Hari Author-X-Name-Last: Sharma Title: Use of known population median of study variable for elevated estimation of population mean Abstract: In this research, we proposed a new enhanced estimator of population mean of primary variable utilising the acquaintance on the known median of the main variable. We perused the features of the distribution of the proposed estimator till the approximation of order one. The articulated estimator is collated with the estimators in competition of the population mean, and the prerequisites of the suggested estimator to be more efficient over competing are derived. These conditions are put to the proof using the numerical example. The efficiencies are compared in terms of the mean squared errors. Journal: Int. J. of Applied Management Science Pages: 28-41 Issue: 1 Volume: 15 Year: 2023 Keywords: main variable; modified ratio estimator; mean squared error; percentage relative efficiency. File-URL: http://www.inderscience.com/link.php?id=128300 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:1:p:28-41 Template-Type: ReDIF-Article 1.0 Author-Name: Habiba Abdessalem Author-X-Name-First: Habiba Author-X-Name-Last: Abdessalem Author-Name: Aida Bouzir Author-X-Name-First: Aida Author-X-Name-Last: Bouzir Author-Name: Saloua Benammou Author-X-Name-First: Saloua Author-X-Name-Last: Benammou Title: Determinants of Tunisian multimodal travel choice: a hybrid model based on multinomial logit and wavelet transform Abstract: This paper aims to analysing the Tunisian multimodal travel choice in the Sahel region using a hybrid model based on multinomial logit and wavelet thresholding. Data are collected through a questionnaire. Thereby, it is found that travellers who choose 'taxi-metro' give a great importance to the trip comfort and the value of time but they do not give any to the travel cost. However, the passengers choosing 'taxi-bus' and 'taxi-hire' are less interested in the travel comfort than the trip cost. The results also underline the positive impact of transfer facilities including 'restroom', 'seat', 'information', 'security agent' and 'security tools' on passengers' comfort perception. For bus and hire transit, it is found that an adequate level of cleanliness, an easy access to hire station, the presence of restaurants and shelters and a minimum degree of crowdedness reduces significantly the burden of traveling and increases the using of 'taxi-bus' and 'taxi-hire' rather than 'taxi-metro'. Journal: Int. J. of Applied Management Science Pages: 192-215 Issue: 3 Volume: 15 Year: 2023 Keywords: multimodal choice; transit passengers; transfer facilities; multinomial logit model; wavelet thresholding; hybrid model. File-URL: http://www.inderscience.com/link.php?id=133677 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:3:p:192-215 Template-Type: ReDIF-Article 1.0 Author-Name: Pranesh Singh Bhoodhoo Author-X-Name-First: Pranesh Singh Author-X-Name-Last: Bhoodhoo Author-Name: Amir Hossein Ghapanchi Author-X-Name-First: Amir Hossein Author-X-Name-Last: Ghapanchi Title: Lessons learnt from stakeholder engagement in public infrastructure projects in Australia Abstract: Stakeholder engagement has always been a field of concern for project managers. As part of economic growth and better living conditions, governments are investing massively on public infrastructure projects, pressing the urge for project success. This paper seeks to extract lessons learnt from stakeholder engagement in public infrastructure projects in Australia. This study extracts 21 lessons regarding stakeholder management in public infrastructure project from its 3 case studies, and proposes a framework of lessons. These 21 lessons are categorised into conflict/dispute, communication, methodology/tools/techniques, legislation, resource management, relationships/attitude/behaviour, health and safety and project team. To the best of our knowledge, there is no article that has specifically looked into exploring a big picture taxonomy of lessons learnt from stakeholder engagement in public infrastructure projects through multiple case studies. Journal: Int. J. of Applied Management Science Pages: 167-191 Issue: 3 Volume: 15 Year: 2023 Keywords: project management; stakeholder management; stakeholder engagement; public infrastructure projects. File-URL: http://www.inderscience.com/link.php?id=133678 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:3:p:167-191 Template-Type: ReDIF-Article 1.0 Author-Name: Abdelrahman AbuSerriya Author-X-Name-First: Abdelrahman Author-X-Name-Last: AbuSerriya Author-Name: Hatem Abu Hamed Author-X-Name-First: Hatem Abu Author-X-Name-Last: Hamed Author-Name: Salah R. Agha Author-X-Name-First: Salah R. Author-X-Name-Last: Agha Title: Municipal water supplies efficiencies in Gaza Strip: a data envelopment analysis approach Abstract: This paper reports the findings of a research carried out to evaluate the efficiency of municipal water supply systems using Data Envelopment Analysis (DEA). Input and output variables needed for DEA were identified using literature review and questionnaires. Input variables considered in this paper include Number of Connections (NC), Length of Water Network (LWN), Number of Employees (NE) and Maintenance and Operation Costs (MOC), while Total Revenues (TR) and Number of People Served (NPS) were used as output variables. Values of these variables were obtained for the existing 25 municipalities for the years of 2015, 2016 and 2017 and the averages of these variables were calculated and used in the model. The paper uses Charnes, Cooper and Rhodes (CCR) model and Banker, Chames and Cooper (BCC) model. Results indicate that length of water network and maintenance and operation costs were the major sources of inefficiencies. Journal: Int. J. of Applied Management Science Pages: 42-56 Issue: 1 Volume: 15 Year: 2023 Keywords: efficiency; data envelopment analysis; water services; municipalities. File-URL: http://www.inderscience.com/link.php?id=128304 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:1:p:42-56 Template-Type: ReDIF-Article 1.0 Author-Name: Queen Emwenkeke Usadolo Author-X-Name-First: Queen Emwenkeke Author-X-Name-Last: Usadolo Author-Name: Yvonne Brunetto Author-X-Name-First: Yvonne Author-X-Name-Last: Brunetto Author-Name: Silvia Nelson Author-X-Name-First: Silvia Author-X-Name-Last: Nelson Author-Name: Patrick Gillett Author-X-Name-First: Patrick Author-X-Name-Last: Gillett Title: The mediating impact of motive fulfilment on the relationship between supervisors and volunteers' intention to stay Abstract: In this study, the effects of relationships with immediate supervisors, or Leader-Membership Exchange (LMX), on volunteers' intentions to stay with their organisations through motive fulfilment are examined. Data were collected from 213 volunteers working in community non-profit organisations in Queensland, Australia, and hypotheses tested with simple and multiple linear regression analysis. The findings show that the fulfilment of values, understanding, enhancement, social, and career motives partially mediated the effect of LMX on volunteers' intentions to stay. The results indicate that motive fulfilment is important in promoting positive workplace outcomes by enhancing volunteer-supervisor relationships. Journal: Int. J. of Applied Management Science Pages: 1-27 Issue: 1 Volume: 15 Year: 2023 Keywords: volunteers; leader-member exchange; motive fulfilment; intention to stay and NPOs. File-URL: http://www.inderscience.com/link.php?id=128305 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:1:p:1-27 Template-Type: ReDIF-Article 1.0 Author-Name: Mohit Beniwal Author-X-Name-First: Mohit Author-X-Name-Last: Beniwal Author-Name: Archana Singh Author-X-Name-First: Archana Author-X-Name-Last: Singh Author-Name: Nand Kumar Author-X-Name-First: Nand Author-X-Name-Last: Kumar Title: A comparative study of static and iterative models of ARIMA and SVR to predict stock indices prices in developed and emerging economies Abstract: Predicting the stock market is a complex and strenuous task. Moreover, the stock market time series is nonlinear, volatile, dynamic, and chaotic. The efficient market hypothesis (EMH) and random walk hypothesis (RWH) state that it is futile to predict the stock market. Auto-regressive integrated moving average (ARIMA) and support vector regression (SVR) are popular methods in time series forecasting. This study empirically compares static and iterative models of ARIMA and SVR's ability to predict stock market indices in developed and emerging economies. Five global stock indices, two from emerging and three from developing economies, are predicted. In the long-term, in contrast to EMH and RWH, the results show that the SVR has predictable power. Further, the SVR has better predictability in emerging economies than in developed ones in long-term forecasting. The market shows efficient behaviour in daily prediction, and the naïve model is the best performer. Additionally, the ARIMA model is equivalent to the naïve model in daily and long-term prediction. Journal: Int. J. of Applied Management Science Pages: 352-371 Issue: 4 Volume: 15 Year: 2023 Keywords: SVR; support vector regression; time series analysis; predicting stock prices; auto-regressive integrated moving average; ARIMA; emerging economies; EMH; efficient market hypothesis; RWH; random walk hypothesis. File-URL: http://www.inderscience.com/link.php?id=134452 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:4:p:352-371 Template-Type: ReDIF-Article 1.0 Author-Name: Julia T. Thomas Author-X-Name-First: Julia T. Author-X-Name-Last: Thomas Author-Name: Mahesh Kumar Author-X-Name-First: Mahesh Author-X-Name-Last: Kumar Title: An optimal Bayesian acceptance sampling plan using decision tree method Abstract: Acceptance sampling plans are widely used inspection policies for the quality assurance models in supply chain management systems. In this paper, the authors propose a decision-making model to obtain the optimal decision about a lot undergoing an acceptance sampling plan. In the first stage, the proportion of defectives is assumed to follow the Poisson distribution. Bayesian inference is used to model the decision outcomes of the sampling plan, which are acceptance, rejection or further inspection policies. The decision tree method along with backward induction is used in the second stage to determine the expected cost of various decisions about the lot. An optimal decision on a lot is evaluated based on minimal rejections allowed such that the cost incurred is minimum. The efficiency of the proposed model is compared with sampling models under identical conditions and numerical examples are provided to illustrate the application of the decision model. Journal: Int. J. of Applied Management Science Pages: 311-325 Issue: 4 Volume: 15 Year: 2023 Keywords: acceptance sampling plan; Bayesian inference; Poisson distribution; decision tree method. File-URL: http://www.inderscience.com/link.php?id=134457 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:4:p:311-325 Template-Type: ReDIF-Article 1.0 Author-Name: Jakia Parvin Author-X-Name-First: Jakia Author-X-Name-Last: Parvin Author-Name: Mahfuzulhoq Chowdhury Author-X-Name-First: Mahfuzulhoq Author-X-Name-Last: Chowdhury Title: A machine learning-based credit lending eligibility prediction and suitable bank recommendation: an Android app for entrepreneurs Abstract: In Bangladesh, men and women are entering business not only to earn money but also to change their social conditions. Capital for conducting business is a big challenge for both male and female entrepreneurs. However, due to the lack of a proper loan eligibility system, both male and female entrepreneurs faced several problems regarding getting loans. Most entrepreneurs are unwilling to take loans from banks because their loan applications are rejected for various reasons. To overcome these challenges, in this paper, an automated recommendation system has been provided in a mobile application. This paper collects a real-time dataset for loan approval prediction systems. The system also develops a prediction model using machine learning algorithms that predict an entrepreneur's loan eligibility. The android application offers recommendations for a suitable bank for an eligible entrepreneur based on the prediction model and user data. The presented results confirm the necessity of our proposed system. Journal: Int. J. of Applied Management Science Pages: 238-257 Issue: 3 Volume: 15 Year: 2023 Keywords: loan; entrepreneur; prediction; classification algorithm; machine learning; mobile application. File-URL: http://www.inderscience.com/link.php?id=133698 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:3:p:238-257 Template-Type: ReDIF-Article 1.0 Author-Name: Monika Poriye Author-X-Name-First: Monika Author-X-Name-Last: Poriye Author-Name: Shuchita Upadhyaya Author-X-Name-First: Shuchita Author-X-Name-Last: Upadhyaya Title: DNA-SKA: a DNA congruous secure symmetric key generation algorithm Abstract: An efficient algorithm DNA-based Symmetric Key Algorithm (DNA-SKA) for generating secret keys for sensor nodes is proposed in this paper. The key feature of the proposed algorithm is the usage of a DNA sequence as an initial key which is proffered to be selected from National Council of Biotechnological Information (NCBI) database available publically. Authentication process is required to make a secure communication between nodes. The Base Station then provides both nodes with two unique DNA strands generated by the unwinding of a single DNA molecule selected from NCBI database. The nodes then perform a simple but ingenious mechanism on the strands to obtain a similar symmetric key to be used for further encryption of the data to be communicated between the nodes. Computationally, it is a light-weight algorithm and better suitable for devices like sensor nodes because of their limited computing resources. Journal: Int. J. of Applied Management Science Pages: 90-101 Issue: 2 Volume: 15 Year: 2023 Keywords: wireless sensor networks; DNA computing; DNA replication; DNA cryptography; DNA steganography. File-URL: http://www.inderscience.com/link.php?id=131668 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:2:p:90-101 Template-Type: ReDIF-Article 1.0 Author-Name: Madapuri Rudra Kumar Author-X-Name-First: Madapuri Rudra Author-X-Name-Last: Kumar Author-Name: Vinit Kumar Gunjan Author-X-Name-First: Vinit Kumar Author-X-Name-Last: Gunjan Author-Name: Mohd Dilshad Ansari Author-X-Name-First: Mohd Dilshad Author-X-Name-Last: Ansari Title: Machine learning-based-HR appraisal system (ML-APS) Abstract: Appraisal systems hold critical importance in organisational human resource management. The way HR departments have developed over the period to the recent trends of AI-based human resource management systems and practices reflect on the emerging importance of effective HRM. In this present work, one of the key functionalities of the HRM process, the Appraisal system, is focused upon. This work presents a comprehensive model of appraisal system that relies on the machine learning solution for predicting evaluating the appraisal score. The developed model is trained with SVM classifier and is tested with 600+ records for evaluation. The precision and recall values indicated by the test results reflect that the model is potential and if more effectively pursued in terms of training and incorporating more in-depth analysis, the model can be a sustainable solution for human resource appraisal system. Journal: Int. J. of Applied Management Science Pages: 102-116 Issue: 2 Volume: 15 Year: 2023 Keywords: machine learning-based appraisal system; ML-APS; 360-degree performance system analysis. File-URL: http://www.inderscience.com/link.php?id=131669 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:2:p:102-116 Template-Type: ReDIF-Article 1.0 Author-Name: Meghna Dhalaria Author-X-Name-First: Meghna Author-X-Name-Last: Dhalaria Author-Name: Ekta Gandotra Author-X-Name-First: Ekta Author-X-Name-Last: Gandotra Title: Binary and multi-class classification of Android applications using static features Abstract: Android has dominated the smart phone market in recent years. As a result, there is a massive increase in Android applications. Due to the increasing number of applications and users' dependence on these, Android has become a prime target for attackers. Hence, there is a need for new malware detection methods. Machine learning algorithms are being used for this purpose. This paper proposes a framework which is capable of performing binary and multi-classification of Android applications. Machine learning algorithms are used on a self-created dataset to classify Android applications into malicious and benign. Further, the malicious applications are classified into their families using the same machine learning algorithms. It is concluded that the accuracy of classification of malicious applications into the families gives very less accuracy (86.70% achieved by Random Forest) as compared to the binary classification accuracy (96.50% achieved by Random Forest). Journal: Int. J. of Applied Management Science Pages: 117-140 Issue: 2 Volume: 15 Year: 2023 Keywords: android malware; binary classification; deep learning; machine learning; multiclass classification; static features. File-URL: http://www.inderscience.com/link.php?id=131670 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:2:p:117-140 Template-Type: ReDIF-Article 1.0 Author-Name: Gaurav Agrawal Author-X-Name-First: Gaurav Author-X-Name-Last: Agrawal Author-Name: Devendra Kumar Author-X-Name-First: Devendra Author-X-Name-Last: Kumar Author-Name: Mayank Singh Author-X-Name-First: Mayank Author-X-Name-Last: Singh Title: Accessing the usability and accessibility of Indian higher education institution's websites Abstract: The internet has become the most important and easiest tool to access digital information about any organisation. Organisations use websites to show their presence on the World Wide Web and these websites are the first door to the people to acquire information about their organisation. In the developing country like India where digitisation is in the very early phase, the internet is widely used by the students to access the websites of higher education institutions to access information and these websites form the first impression about the college. To cater the need of every section of society, these websites must be universally accessible to normal as well as to disabled people. The purpose of this study is to investigate whether the websites of the institution affiliated to Uttarakhand Technical University, Dehradun, India comply with the standards of accessibility and usability. The study is conducted by using the online evaluation tool. The results indicate that all websites have low usability and the websites show low compliance with Web Content Accessibility Guidelines version 2 (WCAG 2.0), the majority of websites have an accessibility problem. Journal: Int. J. of Applied Management Science Pages: 141-150 Issue: 2 Volume: 15 Year: 2023 Keywords: web usability; web accessibility; higher education; WCAG 2.0. File-URL: http://www.inderscience.com/link.php?id=131671 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:2:p:141-150 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammad Naushad Author-X-Name-First: Mohammad Author-X-Name-Last: Naushad Author-Name: Shaha Faisal Author-X-Name-First: Shaha Author-X-Name-Last: Faisal Title: Intellectual capital efficiencies and performance of SMEs in KSA Abstract: The advent of innovations and knowledge-based businesses has expanded the importance of Intellectual Capital (IC) in their performance. IC is considered as an assortment of intangible assets. Small- and Medium Enterprises (SMEs), usually characterised by fewer tangible and higher intangible assets, have vast untapped potential to gain a sustainable competitive advantage by utilising IC. The present paper is an endeavour to understand the impact of IC on SMEs' performance listed in the parallel market of Saudi Arabia called NOMU. The study measured the IC efficiency among the SMEs in KSA for the period from 2016 to 2018. The study, which is grounded in strong theoretical roots with a validated methodology, also identified IC's impact on profitability and productivity for the said duration among the quoted sector. Value Added Intellectual Coefficient (VAIC) was utilised as a proxy measure for IC. Return on Assets (ROA) and Assets to Turnover Ratio (ATO) has been used as the proxy measure of profitability and productivity, respectively. The Ordinary Least Square (OLS) regression method has been deployed to draw the impact of VAIC and its components upon SMEs' profitability and productivity. The results were statistically significant, indicating that VAIC impacts profitability and productivity. However, the components of VAIC failed to draw a significant impact on productivity. The study findings would help SMEs owners take note of IC and its components in reaching higher profitability and productivity levels. Journal: Int. J. of Applied Management Science Pages: 151-165 Issue: 2 Volume: 15 Year: 2023 Keywords: intellectual capital; SMEs; VAIC; intangible assets; Saudi Arabia. File-URL: http://www.inderscience.com/link.php?id=131672 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:injams:v:15:y:2023:i:2:p:151-165