Information Resource Management Research Articles

Flexible Work Arrangements, Stress, Work-Life Balance, and Motivation: their Implications on Junior High School Teachers in the Depok Region

This study aims to analyse Flexible Work Arrangements, Stress, Work-Life Balance, and Motivation and Their Implications on Junior High School Teachers in the Depok Region. The research provides both theoretical and managerial implications as inputs for Work-Life Balance influenced by Flexible Work Arrangements and Stress as exogenous variables through Motivation as a moderating variable. The population in this study comprises Junior High School Teachers in the Depok Region, utilizing Snowball Sampling technique in an effort to gather respondents numbering more than 100. Data from these respondents are then analysed for their fit with the research model developed from the theoretical framework using SmartPLS SEM analysis. The results of this study are expected to: (1) Analyse and test all factors influencing Motivation and Work-Life Balance, namely Flexible Work Arrangements and stress, (2) Provide additional information for the Depok City Government for policy formulation regarding assessment and enhancement of motivation as well as efforts to improve teachers' work-life balance for the better, (3) Provide additional information and knowledge for Human Resource Management, especially its implications for enhancing Motivation and Work-Life Balance in schools. The hypothesis testing results prove that: 1) Flexible Work Arrangements have a positive and significant effect on work motivation. 2) Stress has a positive and significant effect on work motivation. 3) Motivation has a positive and significant effect on work-life balance. 4) Flexible Work Arrangements have a positive and significant effect on work-life balance. 5) Stress does not affect work-life balance. 6) Flexible Work Arrangements indirectly have a positive and significant effect on work-life balance through motivation. 7) Stress indirectly has a positive and significant effect on work-life balance through motivation.

Research on Alibaba company’s Digital Human Resource management and Recruitment Information Platform: A systematic case study

In the 21st century, As data-based human resource management, AI HRM technologists and digital recruitment have become a major trend in the development of enterprises, the multi-faceted video interview artifact will help enterprises to digitally transform their recruitment and create a revolution in video interview efficiency. Although Human resource management, digital recruitment, and the training of talents have gained a lot of experience and methodology. Moreover, This study also uses the Documentary analysis and TAM theoretical model for analysis. The aspect of digital human resource management includes many factors. Alibaba company starts from the human business and human resource meets the end of the business. Alibaba company defines five key end-to-end digital processes and specifications here: employee onboarding, employee deployment, and employee satisfaction. Performance-based compensation, employee ability training, and employee turnover optimization. To sum up, The research of this paper mainly uses the mixed method of qualitative analysis and quantitative mixed analysis to conduct research and analysis, and uses excel or SPSS 27 software to perform ANOVA analysis on the sample data, and concludes the importance of human resources digitization and recruitment to Ali-baba company. The findings of the study not only not only deepen the research on the development of digital human resource management in enterprises, but also provide valuable reference for the research and development of AI technology and new digital technology for human resource management and recruitment platforms.

Assessing the Relationship between Technological Factors and the Implementation of Human Resource Information System: A survey in the Municipal, Metropolitan, and District Assemblies in the Upper West Region of Ghana

Over the years, public sector organization such as Metropolitan, Municipal, and District Assemblies (MMDAs) in Ghana have been challenged by a significant number of factors that affect the implementation of Human Resource Management Information Systems (HRISs). The study focuses on assessing the technological factors affecting the implementation of the HRIS in the MMDAs in the Upper West Region of Ghana. The philosophical foundation of the study was positivism. A cross-sectional survey was employed in the study as part of a quantitative research design. The target population comprised of 187 Line managers. The study used a non-probability sampling technique known as purposive sampling. Self-administered questionnaires were used to collect primary data. The study also embraced descriptive and inferential statistics. Bivariate regression analysis and correlation coefficient were used to establish causal relationships between variables. Stepwise regression was also used to determine the most influential variables in implementing of HRIS. It was concluded that IT Infrastructure and Compatibility had a moderate level of acceptance as factors that affect the implementation of the HRIS. In contrast, Quality Information, System Quality, and Complexity had a low level of acceptance. The study also concluded that Complexity, Quality Information, Compatibility and System Quality had correlated with the acceptance of the HRIS, whereas IT infrastructure did not correlate with the acceptance of the HRIS. Lastly, it was concluded that IT Infrastructure, Complexity, Quality Information, Compatibility, and System Quality did correlate with the Effectiveness of the HRIS. The study recommends that, HRIS Software adopted and implemented at the LGS and its Agencies must be user-friendly. The LGS and its Agencies do not have a guide that support new technology implementation such as the HRIS. Hence the need to adopt the guide offered in this study.

Librarians' Understanding and Support for Legal Entity Universities: Case Study of the Transition of UIN Syarif Hidayatullah Jakarta to Become a Legal Entity State University

University rankings and changes in status of international standards and quality universities toward the Legal Entity State Universities have become a phenomenon in various universities in Indonesia. The university changed its status to Legal Entity State Universities in order to meet and improve its current global vision, mission, and goals. This article examines the librarians image in supporting their universities toward becoming Legal Entity State Universities. This research aims to analyze the understanding and support of librarians toward higher education in the context of Legal Entity State Universities. This research uses a qualitative approach. The research results found that librarian’s support for changes in university status could increase campus productivity. Involving librarians in planning and implementing status changes will influence library service innovation and information resource management. This research has important implications in revealing librarians’ understanding and support for the plan to change the status of UIN Syarif Hidayatullah Jakarta from Public Service Agency State University to Legal Entity State University. The results of this research can be beneficial for UIN Syarif Hidayatullah policymakers to provide better and more equitable direction to the entire academic community, including librarians.
 Keywords: Legal Entity State University, librarian support, higher education

Особенности формирования системы управления информационными ресурсами организации

The article deals with issues related to the peculiarities of the formation of information resource management systems, which is an urgent and significant problem for the modern economic system. To disclose the problem of research, the paper considers the concept of modern information resources, describes the characteristics of information resources and reveals different approaches to the formation of information resource management systems. The study is implemented by implementing such methods of scientific knowledge, as information analysis, synthesis and synthesis of information, structuring. The con-clusion of the work provides brief conclusions on the results of the study and voiced current issues requiring further reflection

Retrospective Study of Lung Cancer: Evolution in 16 Years in the Burgos Region.

Background: This study investigates the evolution of lung cancer in the population of Burgos over more than a decade, focusing on key variables such as age, gender, histology, and stage of diagnosis. The aim is to understand how incidence rates and patterns have changed over time, especially in terms of early diagnosis. Methods: Retrospective data were collected from the Burgos University Hospital using histological or clinicoradiological methods. This data collection approach enabled a comprehensive examination of lung cancer trends in the province. Results: The results reveal an overall decrease in lung cancer incidence rates in men, offset by a steady increase in women. Histological analysis highlights a significant increase in adenocarcinoma, accounting for 43% of cases in the last year studied. Despite diagnostic advances, almost half of the diagnoses were made at stage IV, with no statistically significant change from previous years, highlighting persistent challenges in early diagnosis. Conclusions: The findings will not only inform resource management and prevention but could also have a significant impact on improved screening strategies and future lung cancer research.

Satellite-Derived Indicators of Drought Severity and Water Storage in Estuarine Reservoirs: A Case Study of Qingcaosha Reservoir, China

Estuarine reservoirs are critical for freshwater supply and security, especially for regions facing water scarcity challenges due to climate change and population growth. Conventional methods for assessing drought severity or monitoring reservoir water level and storage are often limited by data availability, accessibility and quality. We present an approach for monitoring estuarine reservoir water levels, storage and extreme drought via satellite remote sensing and waterline detection. Based on the CoastSat algorithm, Landsat-8 and Sentinel-2 images from 2013 to 2022 were adopted to extract the waterline of Qingcaosha Reservoir, the largest estuarine reservoir in the world and a key source of freshwater for Shanghai, China. This study confirmed the accuracy of the satellite-extracted results through two main methods: (1) calculating the angle of the central shoal slope in the reservoir using the extracted waterline data and measured water levels and (2) inverting the time series of water levels for comparison with measured data. The correlation coefficient of the estimated water level reached ~0.86, and the root mean square error (RMSE) of the estimated shoal slope was ~0.2°, indicating that the approach had high accuracy and reliability. We analyzed the temporal and spatial patterns of waterline changes and identified two dates (21 February 2014 and 15 October 2022) when the reservoir reached the lowest water levels, coinciding with periods of severe saltwater intrusions in the estuary. The extreme drought occurrences in the Qingcaosha Reservoir were firstly documented through the utilization of remote sensing data. The results also indicate a strong resilience of the Qingcaosha Reservoir and demonstrate that the feasibility and utility of using satellite remote sensing and waterline detection for estuarine reservoir storage can provide timely and accurate information for water resource assessment, management and planning.

Assessing Metal Use and Scarcity Impacts of Vehicle Gliders

AbstractThis study assesses the metal composition of two vehicle gliders, configured with different equipment levels and evaluates the risk of short and long-term metal scarcity. Entropy analysis is also used for insights on secondary metal recovery strategies. Fifty-five metals are evaluated, with gold, copper, bismuth, lead, molybdenum, and certain rare-earth metals (REMs) subject to the largest supply risks. Differences in equipment levels significantly impact the short-term supply risk for specific metals. Entertainment and communications equipment contain significant amounts of REMs, whereas mirrors and electrical infrastructure contain considerable shares of gold, silver and copper. Some metals are concentrated in a few components while some are dispersed across thousands, impacting recycling opportunities. The broad metal demand of the gliders underscores the automotive industry's role in supply risks for its own manufacturing needs and other societal domains. This emphasizes the significance of comprehensively evaluating metal requirements beyond powertrains for informed resource management.

Job satisfaction in the armed forces: Differences among ranks

Human resource management has attracted significant attention among researchers of public management. It is increasingly accepted that committed and satisfied employees are strategic resources in any organization. The idiosyncrasies of the armed forces and the professionalization processes they have undergone necessitate a study of the attitudes of military personnel towards work in the sector. This paper analyses the determinants of job satisfaction in the military. Three factors (“Work itself”, “Economic aspects” and “Personal relationships”) are identified based on data from the International Social Survey Programme (ISSP). Both the composition and the impact of these factors on job satisfaction vary according to the hierarchical rank of a worker. The findings confirm the importance of differentiated human resources policies that take into account the hierarchical diversity of the military. Our results provide new evidence and valuable practical information for human resource management in the armed forces. We provide policymakers and managers of the military sector with recommendations that allow them to reinforce the ability of the armed forces to attract, retain and motivate talent.

Eliminating Non-Value-Added Activities and Optimizing Manufacturing Processes Using Process Mining: A Stock of Challenges for Family SMEs

Family small and medium enterprises (FSMEs) differ from non-family SMEs regarding leadership type, human resource management practices, innovation orientation, change management, information and communication technology deployment, process maturity, and resource availability. These differences present challenges when leading any change. Process mining (PM) tools can optimize process value and eliminate non-added-value activities in FSMEs based on “Event Logs”. The present study investigates how a PM project is implemented in an FSME operating in the agri-food sector, focusing on challenges faced in every project phase to extract the most appropriate process that eliminates all sources of waste and bottleneck cases. Drawing upon the L*Lifecycle methodology combined with quality and lean management tools such as the fishbone diagram, Pareto diagram, and overall equipment efficiency (OEE), this study applied a PM project to a manufacturing process for an FSME operating in the agri-food sector. To achieve theoretical production capacity (TPC) and customer satisfaction, the method was analyzed and optimized using Disco and ProM toolkits. The results analysis using Disco and ProM toolkits gave clues about the organizational and technical causes behind the manufacturing process’s inefficiency. First, OEE showed that the studied FSME is struggling with equipment availability. Then, the implementation of the L*Lifecycle methodology allowed for the identification of five critical causes. An action plan to eliminate causes was proposed to the FSME managers.

Evaluation of Historic Trends for Monthly, Seasonal, and Annual Rainfall Series of Tenkasi, Tamil Nadu, India

Analyzing the variability and trends of rainfall plays a major role in water resource planning and management. Changes in rainfall patterns significantly influence the water availability in the irrigation structures and agronomical practices of crops.  This study aimed to investigate the trends and estimate the magnitudes of monthly, seasonal, and annual rainfall series in Tenkasi, Tamil Nadu, India, using 49 years of rainfall data from 1971 to 2019. Sen’s Innovative trend analysis (ITA) method, Mann-Kendall (MK), and Simple Linear Regression (SLR) test were applied to assess the trends at 5 and 10 % significance levels. Trend magnitudes were estimated by Sen’s slope estimator (SSE) and SLR method. Changes in rainfall magnitude with mean values in percentage were estimated for all three slope estimation methods. The results revealed that the ITA method detected more significant trends of rainfall series over other methods. Significant downward trends were exhibited by October and north east monsoon (NEM) rainfall series had a trend magnitude of -0.43 mm/year and -0.04 mm/year. The percentage change in magnitude of the trend from mean values for October and the NEM series was -11.5% and -0.39%. Sub-trends within the October and NEM rainfall series showed that the low rainfall sub-series exhibited no trend, medium and high rainfall sub-series showed a downward trend. This study concluded that, in comparison to traditional trend analysis methods, the ITA method demonstrated a more rigorous investigation of trends. The significant decrease in rainfall during the NEM necessitates greater attention to water resources planning and management, serving as valuable scientific information for both crop planning and water resource management.

Broad-scale genetic population connectivity in the Moreton Bay Bug (Thenus australiensis) on Australia’s east coast

Understanding population connectivity helps inform resource and conservation managers about appropriate boundaries for management units. However, for many species facing recent increases in fishing or environmental pressure, accurate information on population structure is lacking. Reef Bugs (Thenus australiensis), commonly known as Moreton Bay Bugs, are iconic shovel-nosed lobsters in northern Australia and an increasingly important fisheries resource. Around 80% of landings occur in the Queensland East Coast Otter Trawl Fishery (ECOTF) where the first stock assessment of the species is underway. However, knowledge about population structure to inform stock assessment is lacking. We used genome complexity reduction-based sequencing to characterise high-quality Single Nucleotide Polymorphisms (SNPs) used to evaluate population structure among three management zones of the ECOTF. Post-filtering, a total of 3,031 SNPs were used to infer no genetic differences among locations indicating strong genetic population connectivity. The presence of a single panmictic population was further supported by cluster and kinship analyses. Broad-scale genetic connectivity likely results from pelagic larval dispersal due to limited adult movements. Findings of high gene flow among connected populations indicate a single biological stock of T. australiensis on Australia’s east coast and will inform future fisheries management initiatives.

Coupling state‐of‐the‐art modelling tools for better informed Red List assessments of marine fishes

Abstract In the face of biodiversity loss worldwide, it is paramount to quantify species' extinction risk to guide conservation efforts. The International Union for the Conservation of Nature (IUCN)'s Red List is considered the global standard for evaluating extinction risks. IUCN criteria also inform national extinction risk assessments. Bayesian models, including the state‐of‐the‐art JARA (‘Just Another Red List Assessment’) tool, deliver probabilistic statements about species falling into extinction risk categories, thereby enabling characterisation and communication of uncertainty in extinction risk assessments. We coupled the state‐of‐the‐art VAST (‘Vector Autoregressive Spatio‐Temporal’) modelling tool and JARA, for better informed Red List assessments of marine fishes. In this framework, VAST is fitted to scientific survey catch rate data to provide indices to JARA whose uncertainty is propagated to JARA outcomes suggesting extinction risk categories (under the population reduction criterion). In addition, VAST delivers a valuable habitat assessment to better understand what may be driving extinction risk in the study region. Here, we demonstrate the coupled VAST‐JARA modelling framework by applying it to five contrasting North Sea species, with or without a quantitative stock assessment and with different conservation statuses according to the latest global Red List assessments. The North Sea application coupled with previous assessments and studies suggest that, among the three elasmobranchs, starry ray is in most need of urgent research (and conservation actions where appropriate), followed by spurdog, while lesser‐spotted dogfish is increasing in biomass. Moreover, both the VAST‐JARA modelling framework and previous research indicate that, while European plaice is not of conservation concern, cod has likely met the IUCN criteria for being listed as Endangered recently. Synthesis and applications. The predictions of the VAST‐JARA modelling framework for North Sea species, including JARA output and VAST habitat assessment, constitute valuable supporting information to make interpretations based on Red List guidelines, which will help decision‐makers in their next North Sea Red List assessment. We foresee applications of the modelling framework to assist Red List assessments of numerous marine fishes worldwide. Our modelling framework has many potential advantageous uses, including informing resource management about climate change impacts on species' extinction risks.

Long-Term Spatiotemporal Investigation of Various Rainfall Intensities over Central India Using EO Datasets

This study involved an investigation of the long-term seasonal rainfall patterns in central India at the district level during the period from 1991 to 2020, including various aspects such as the spatiotemporal seasonal trend of rainfall patterns, rainfall variability, trends of rainy days with different intensities, decadal percentage deviation in long-term rainfall patterns, and decadal percentage deviation in rainfall events along with their respective intensities. The central region of India was meticulously divided into distinct subparts, namely, Gujarat, Daman and Diu, Maharashtra, Goa, Dadra and Nagar Haveli, Madhya Pradesh, Chhattisgarh, and Odisha. The experimental outcomes represented the disparities in rainfall distribution across different districts of central India with the spatial distribution of mean rainfall ranges during winter (2.08 mm over Dadra and Nagar Haveli with an average of 24.19 mm over Odisha), premonsoon (6.65 mm over Gujarat to 132.89 mm over Odisha), monsoon (845.46 mm over Gujarat to 3188.21 mm over Goa), and post-monsoon (30.35 mm over Gujarat to 213.87 mm over Goa), respectively. Almost all the districts of central India displayed an uneven pattern in the percentage deviation of seasonal rainfall in all three decades for all seasons, which indicates the seasonal rainfall variability over the last 30 years. A noticeable variation in the percentage deviation of seasonal rainfall patterns has been observed in the following districts: Rewa, Puri, Anuppur, Ahmadabad, Navsari, Chhindwara, Devbhumi Dwarka, Amreli, Panch Mahals, Kolhapur, Kandhamal, Ratnagiri, Porbandar, Bametara, and Sabar Kantha. In addition, a larger number of rainy days of various categories occurred in the monsoon season in comparison to other seasons. A higher contribution of trace rainfall events was found in the winter season. The highest contributions of very light, light rainfall, moderate, rather high, and high events were found in the monsoon season in central India. The percentage of various categories of rainfall events has decreased over the last two decades (2001–2020) in comparison to the third decade (1991–2000), according to the mean number of rainfall events in the last 30 years. This spatiotemporal analysis provides valuable insights into the rainfall trends in central India, which represent regional disparities and the potential challenges impacted by climate patterns. This study contributes to our understanding of the changing rainfall dynamics and offers crucial information for effective water resource management in the region.

Ground Water Resource and Their Characteristics of the Eastcentral Rajmahal Highlands, Jharkhand, India

This study examines the ground water resources and their characteristics of the Eastcentral Rajmahal Highlands in Jharkhand, India, The study aims to provide a comprehensive analysis of the ground water resources in the region and their geographical distribution. The study categorizes the area into four water table classes on the basis of 67 water samples sites, and explores the role of ground water in maintaining agriculture, the economy, and the environment in the region. The results of the study will provide valuable information for water resource management, agricultural planning, and sustainable development in the Eastcentral Rajmahal Highlands in Jharkhand.

Evaluation of Accuracy in Estimating Diameter at Breast Height Based on the Scanning Conditions of Terrestrial Laser Scanning and Circular Fitting Algorithm

A growing societal interest exists in the application of lidar technology to monitor forest resource information and forestry management activities. This study examined the possibility of estimating the diameter at breast height (DBH) of two tree species, Pinus koraiensis (PK) and Larix kaempferi (LK), by varying the number of terrestrial laser scanning (TLS) scans (1, 3, 5, 7, and 9) and DBH estimation methods (circle fitting [CF], ellipse fitting [EF], circle fitting with RANSAC [RCF], and ellipse fitting with RANSAC [REF]). This study evaluates the combination that yields the highest estimation accuracy. The results showed that for PK, the lowest RMSE of 0.97 was achieved when REF was applied to the data from nine scans after noise removal. For LK, the lowest RMSE of 1.03 was observed when applying CF to the data from seven scans after noise removal. Furthermore, ANOVA revealed no significant difference in the estimated DBH from nine scans when more than three scans were used for CF and RCF and more than five for EF and REF. These results are expected to be useful in establishing efficient and accurate DBH estimation plans using TLS for forest resource monitoring.

Leveraging ICESat, ICESat‐2, and Landsat for Global‐Scale, Multi‐Decadal Reconstruction of Lake Water Levels

AbstractLakes provide important water resources and many essential ecosystem services. Some of Earth's largest lakes recently reached record‐low levels, suggesting increasing threats from climate change and anthropogenic activities. Yet, continuous monitoring of lake levels is challenging at a global scale due to the sparse in situ gauging network and the limited spatial or temporal coverage of satellite altimeters. A few pioneering studies used water areas and hypsometric curves to reconstruct water levels but suffered from large uncertainties due to the lack of high‐quality hypsometry data. Here, we propose a novel proxy‐based method to reconstruct multi‐decadal water levels from 1992 to 2018 for both large and small lakes using Landsat images and ICESat (2003–2009) and recently launched ICESat‐2 (2018+) laser altimeters. Using the new method, we evaluate reconstructed levels of 342 lakes worldwide, with sizes ranging from 1 to 81,844 km2. Reconstructed water levels have a median root‐mean‐square error (RMSE) of 0.66 m, equivalent to 57% of the standard deviation of monthly level variability. Compared with two recently reconstructed water level data sets, the proposed method reduces the median RMSE by 27%–32%. The improvement is attributable to the new method's robust construction of high‐quality hypsometry, with a median R2 value of 0.92. Most reconstructed water level time series have a bi‐monthly or higher frequency. Given that ICESat‐2 and Landsat can observe hundreds of thousands of water bodies, this method can be applied to conduct an improved global inventory of time‐varying lake levels and thus inform water resource management more broadly than existing methods.

Trophic lengthening triggered by filamentous, N2-fixing cyanobacteria disrupts pelagic but not benthic food webs in a large estuarine ecosystem.

Eutrophication, increased temperatures and stratification can lead to massive, filamentous, N2-fixing cyanobacterial (FNC) blooms in coastal ecosystems with largely unresolved consequences for the mass and energy supply in food webs. Mesozooplankton adapt to not top-down controlled FNC blooms by switching diets from phytoplankton to microzooplankton, resulting in a directly quantifiable increase in its trophic position (TP) from 2.0 to as high as 3.0. If this process in mesozooplankton, we call trophic lengthening, was transferred to higher trophic levels of a food web, a loss of energy could result in massive declines of fish biomass. We used compound-specific nitrogen stable isotope data of amino acids (CSIA) to estimate and compare the nitrogen (N) sources and TPs of cod and flounder from FNC bloom influence areas (central Baltic Sea) and areas without it (western Baltic Sea). We tested if FNC-triggered trophic lengthening in mesozooplankton is carried over to fish. The TP of cod from the western Baltic (4.1 ± 0.5), feeding mainly on decapods, was equal to reference values. Only cod from the central Baltic, mainly feeding on zooplanktivorous pelagics, had a significantly higher TP (4.6 ± 0.4), indicating a strong carry-over effect trophic lengthening from mesozooplankton. In contrast, the TP of molluscivorous flounder, associated with the benthic food web, was unaffected by trophic lengthening and quite similar reference values of 3.2 ± 0.2 in both areas. This suggests that FNC blooms lead to a large loss of energy in zooplanktivorous but not in molluscivorous mesopredators. If FNC blooms continue to trigger the detour of energy at the base of the pelagic food web due to a massive heterotrophic microbial system, the TP of cod will not return to lower TP values and the fish stock not recover. Monitoring the TP of key species can identify fundamental changes in ecosystems and provide information for resource management.

Investigating the Role of Geography Education in Natural Resource Management

Geography education plays a pivotal role in natural resource management by fostering an understanding of optimal conservation practices. Through comprehensive examination of regional environments and geography, we can gauge the impact of human activities on natural resources and propose sustainable solutions. By increasing environmental awareness, geography education elucidates the repercussions of activities such as deforestation, pollution, biodiversity loss, and climate change. This heightened awareness empowers us to refine policies and management practices, ensuring the judicious utilization and preservation of natural resources. This article underscores the paramount importance of geography education in natural resource preservation. Employing an applied and descriptive approach, the research methodology involves library studies. The findings highlight that geography education establishes vital links between individuals and their environment, facilitating informed resource management decisions. By analyzing regional geography and its influence on natural resources, optimal preservation strategies emerge. For instance, studying precipitation patterns enables efficient water management and drought mitigation. Ultimately, geography education equips us with the knowledge and tools to identify effective resource preservation methods, fostering sustainable utilization practices through enhanced environmental comprehension and spatial awareness.

Employee Acceptance of Human Resource Management Information System: Integrated UTAUT and TTF Model in a Selected Public Firm in Sri Lanka

Aim: In the modern digital world, many companies are moving towards technology-based applications to perform human resource administration work. Employees nowadays are capable of accessing a web-based Human Resource Management Information System (HRMIS) to obtain critical data from recognized techniques such as System Applications and Products (SAP), PeopleSoft, Bann and Lawson. This study aims to investigating the factors affecting the adopting intention of HRMIS in a selected public firm in Sri Lanka.
 Design: Acknowledging the vital concepts on accepting or resisting technology, six components (performance expectancy, effort expectancy, social influence, facilitating conditions, task characteristics, and technology characteristics) from the Unified Theory of Acceptance and Use of Technology (UTAUT) model and the Task Technology Fit (TTF) model were contextualized to investigate the drivers influencing HRMIS adoption intentions in a selected public firm in Sri Lanka. Target population was identified as the Executives, Supervisors/Technical Officers, Clerical and Allied employees of the chosen public company in Sri Lanka. A structured online questionnaire, including 30 items, was used to collect data.
 Findings: Multiple regression analysis results revealed that the factors of Performance Expectation, Task Characteristics, and Technology Characteristics have a positive influence on users’ adoption intention to HRMIS. Effort Expectancy, Social Influence, and Facilitating Conditions had negative influence.
 Implications: The outcomes highlight the necessity of combining TTF components with technology acceptance theories when evaluating the factors influencing acceptance of HRMIS or other information systems. The study's findings will aid management in making the required organizational changes to encourage employees to use the HRMIS application.