International Journal of Applied Management Science (9 papers in press)

Regular Issues

• P-Model of Inventory Optimization for high technology multi-generation products under limited warehouse storage space  
  by Gaurav Nagpal, Udayan Chanda 
  Abstract: This research work puts forward the inventory optimization model for the high technology multi-generation products under the situation of limited warehouse storage space. It is assumed that the manufacturer has an own space which has a lesser opportunity cost of usage as compared to another rented space, that carries higher charges on per unit area basis. Therefore, the manufacturer utilizes the own storage space for the period of time where his own space is sufficient to keep the inventories. When its inhouse space is not sufficient to store all the inventories, it stores the excess inventories at the rented space. While the research work has been done on various demand patterns under such a scenario, there is no research present on the inventory optimization under storage space constraints for the generations of innovative products whose demand follow the Norton Bass Model of Innovation Diffusion. This paper lays down a model for inventory optimization, but also puts forward a few theorems on the dynamics of how the model behaves with the change in innovation effect, imitation effect, with the rent of the leased location and with the storage capacity of own location. Finally, the paper performs numerical illustrations to show the behavior of the proposed model.
  Keywords: Inventory; P-type Inventory System; Storage Space constraints; Optimal inter-replenishment time interval; innovation diffusion. Technology generations.
  
  
• Applying an extended theory of planned behavior to predict Indian customers e-vehicle purchase Intention  
  by Vishal Soodan, Shantanu Saha 
  Abstract: The purpose of this paper is to predict the intentions towards purchase of EVs in India This study has taken Theory of Planned Behavior (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 Behavioral 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.
  Keywords: Commuting; Environmental Concern; Personality; Purchase Intention.
  
  
• Determinants of Tunisian multimodal travel choice: A hybrid model based on multinomial logit and wavelet transform  
  by Habiba Abdessalem, Aida Bouzir, Saloua 
  Abstract: This paper aims to analyzing 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 travelers choosing taxi-metro give a great importance to the trip comfort and the value of time but they do not react to a travel cost. However, the passengers choosing taxi-bus and taxi-hire are less interested in the travel comfort than the trip cost. The results underline also 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.
  Keywords: multimodal choice; transit passengers; transfer facilities; multinomial logit model; wavelet thresholding; hybrid model.
  
  
• Lessons Learnt from Stakeholder Engagement in Public Infrastructure Projects in Australia  
  by Pranesh Singh Bhoodhoo, Amir Hossein Ghapanchi 
  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 categorized into Conflict/dispute, communication, methodology/tools/techniques, legislation, resource management, relationships/attitude/behavior, 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.
  Keywords: Project Management; Stakeholder Management; Stakeholder Engagement; Public Infrastructure Projects.
  
  

Special Issue on: Recent Multidisciplinary Research Advancements in Information Technology and Applied Management for Sustainable Development

• DNA-SKA: A DNA Congruous Secure Symmetric Key Generation Algorithm  
  by Monika Poriye, Shuchita Upadhyaya 
  Abstract: An efficient algorithm DNA-SKA (DNA based Symmetric Key Algorithm) 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.
  Keywords: Wireless sensor networks; DNA Computing; DNA Replication; DNA Cryptography & DNA Steganography.
  
  
• Machine Learning-Based HR Appraisal System (ML-APS)  
  by Madapuri Rudra Kumar, Vinit Kumar Gunjan, Mohd Dilshad Ansari 
  Abstract: Appraisal systems hold critical importance in organizational 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 systems are 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.
  Keywords: Machine learning-based appraisal system; ML-APS; 360 degree performance system analysis.
  
  
• Binary and Multi-class Classification of Android Applications using Static Features  
  by Meghna Dhalaria, Ekta Gandotra 
  Abstract: In recent years, the Android platform has ruled the market of smart mobile phones. As a result, there is a massive increase in Android applications such as banking, education and gaming etc. With the increase in the number of mobile applications and the dependency of users on these, Android has become the prime target of the attackers. Thus, the growth of sophisticated and complex Android malware is increasing that poses various threats such as stealing information, system damage etc. Thus, there is a need to find new ways to detect Android malware. For this purpose, machine learning algorithms have been used to build classifiers. To train such classifiers, there is a need of set of features that could describe the behavior of applications. Thus, we have created two datasets (binary and multiclass datasets) and made these publically available on GitHub. In this paper, a framework has been proposed which is capable of performing binary and multi-classification of Android applications. Static features such as Intents, Permissions, API calls and Command Strings are extracted from the applications and six machine learning algorithms are used to classify these into malicious and benign. Further, the malicious Android 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).
  Keywords: Android malware; Binary classification; Deep learning; Machine learning; Multiclass classification; Static features.
  
  
• Accessing the Usability and Accessibility of Indian Higher education institutions websites  
  by Gaurav Agrawal, Devendra Kumar, Mayank Singh 
  Abstract: The Internet has become the most important and easiest tool to access digital information about any organization. Organizations 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 organization. In the developing country like India where digitization 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 the website has 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.
  Keywords: Web usability; Web Accessibility; Higher Education; WCAG 2.0.
  
  
• Intellectual Capital efficiencies and performance of SMEs in KSA  
  by Mohammad Naushad, Shaha Faisal 
  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 characterized by fewer tangible and higher intangible assets, have vast untapped potential to gain a sustainable competitive advantage by utilizing IC. The present paper is an endeavor 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 utilized 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.
  Keywords: Intellectual Capital; SMEs; VAIC; Intangible Assets; Saudi Arabia.