Turnover Model Research Articles

ORGANIZATIONAL AND ECONOMIC MECHANISM OF LAND RESOURCES USE

One of the main components of natural resources of the agricultural enterprise is land or land resources. After conducting research and analysis of scientific publications, textbooks and manuals of scientific experts, as well as legislative and regulatory framework, the article found that there is no single definition of the essence of the concept of "land resources". On this basis, scientific approaches to the interpretation of the essence of the category "land resources" were summarized and their clarification was proposed. It was established that land resources can be interpreted as the main natural resource used in various sectors of the economy. The types of agricultural land, which include agricultural land: arable land, hayfields, pastures, fallows, perennial plantations, are substantiated. Also considered the main methodological approaches to assessing the effectiveness of the use of land resources of the enterprise, which allow for a comprehensive analysis, justify the conclusions about the effectiveness of agricultural land. The directions to improve the efficiency of land use by optimizing the structure of crops, the use of crop rotation, the creation of land cooperatives and improvement of the mechanism of land protection are formulated. Since the level of efficiency of agricultural land use will depend on the state of productive forces and the growth of the agrarian sector of Ukraine. Attention is paid to the issue of the concept of "land relations", which are an integral part of the economic and legal functioning of agricultural enterprises. In connection with the completion of land reform in Ukraine, the article defines the features of the regulation of land relations in the leading countries of the world. The experience of the United States of America, Canada, Great Britain, the Netherlands, Denmark, Switzerland and other countries is summarized. The peculiarities of functioning of the model of market turnover of agricultural land are analyzed, which led to the conclusion or the need to introduce a liberalized land market in Ukraine.

Capital Turnover Model Based on Genetic Algorithm and Multi-objective Programming

A capital turnover model is established and three main problems are solved. First, select the suppliers that guarantee the production of the enterprise at least as much as needed. Second, develop the most economical material ordering scheme and conduct the scheme analysis. Third, develop the lowest loss material transfer scheme and conduct the scheme analysis. All three problems are planning problems. First, we construct a 0-1 planning model. Then, based on the principle of the lowest total purchase price, we build an objective planning model for the ordering scheme, obtain the most economical ordering scheme by genetic algorithm, and compare it with the least economical scheme and random scheme. Moreover, following the principle of lowest transit loss, we build an objective planning model of transportation scheme based on the most economical ordering solution and compare and analyze with the solution with the highest loss and random solution.

Формирование новой экономики России в условиях трансформации экономических систем

The article reveals the problems of the impact of the economic systems’ transformation on the Russian economy. It is shown that the modern economy, quite expectedly, but unexpectedly rapidly and with unexpected consequences, has entered the stage of transformation of the world economic system and the construction of a new economic order. The impact of sanctions and embargoes on the economic sectors’ development is revealed. The methods and tools for countering sanctions are considered. The economy interdependence of Russia and foreign non-friendly countries is revealed. The failure of a completely liberal model of market regulation of the economy is shown. Changes in the capital turnover model and the required direction for improving the economic model in accordance with modern conditions are disclosed. The research has been carried out on the dynamics of changes in investment and innovation multipliers in the model of economic growth in Russia, problems and directions of development have been identified. The lessons of modern "recent" economic history for the state management of socio-economic development are considered. The problems of transition to a mobilization "sacrificial" economy for Russia and foreign non-friendly states as a transitional economy for the adaptation period of the economic systems of states to transformation processes and the development of a new economic model of the future based on new development concepts are considered. The foundations of a new economic model have been formed. The relevance of the transition from the existing development model "capital - money - capital" to the model "resources - innovations - resources" understood at a new level is shown. The main ideological concepts of the new economic system are considered - ideology, security, sovereignty, policy in economic, social, technological directions. The current essence of the "new" categories of the consolidated development of society, government and business is revealed - usefulness and efficiency, honesty and justice, creativity and responsibility, interests and activity. The ethical foundations of a new economic model formation of Russia are shown, including the Russian fusion of the "new" national mentality and the factors of the new passionarity of Russia. It is determined that Russia has potential behavioral preferences in the effective implementation of programs and projects for the transformation of economic systems.

Predicting Key Predictors of Project Desertion in Blockchain: Experts’ Verification Using One-Sample T-Test

Aim/Purpose: The aim of this study was to identify the critical predictors affecting project desertion in Blockchain projects. Background: Blockchain is one of the innovations that disrupt a broad range of industries and has attracted the interest of software developers. However, despite being an open-source software (OSS) project, the maintenance of the project ultimately relies on small core developers, and it is still uncertain whether the technology will continue to attract a sufficient number of developers. Methodology: The study utilized a systematic literature review (SLR) and an expert review method. The SLR identified 21 primary studies related to project desertion published in Scopus databases from the year 2010 to 2020. Then, Blockchain experts were asked to rank the importance of the identified predictors of project desertion in Blockchain. Contribution: A theoretical framework was constructed based on Social Cognitive Theory (SCT) constructs; personal, behavior, and environmental predictors and related theories. Findings: The findings indicate that the 12 predictors affecting Blockchain project desertion identified through SLR were important and significant. Recommendations for Practitioners: The framework proposed in this paper can be used by the Blockchain development community as a basis to identify developers who might have the tendency to abandon a Blockchain project. Recommendation for Researchers: The results show that some predictors, such as code testing tasks, contributed code decoupling, system integration and expert heterogeneity that are not covered in the existing developer turnover models can be integrated into future research efforts. Impact on Society: This study highlights how an individual’s design choices could determine the success or failure of IS projects. It could direct Blockchain crypto-currency investors and cyber-security managers to pay attention to the developer’s behavior while ensuring secure investments, especially for crypto-currencies projects. Future Research: Future research may employ additional methods, such as a meta-analysis, to provide a comprehensive picture of the main predictors that can predict project desertion in Blockchain.

UKRAINIAN LAND MARKET MODEL – EXCLUSIVE OR «HYBRID» OF THE LATIFUNDIST MODEL?

The article considers topical issues of land reform in Ukraine in the context of the introduction of the Ukrainian model of the agricultural land market (AL). The purpose of the study is a comparative analysis of the official and author's models of the market turnover of ALs in order to increase the strengths and neutralize the weaknesses of the first of them and turn it into an exclusive model, rather than a copy of the worst variants of the baseline models. It is shown that the state model, which is practiced in Israel, China and other countries, is based on lease land relations - between the state, as the owner of the land, and collective agricultural enterprises, and these relations are regulated by the state land authority. It is determined that the farming model, as the most common and effective, has in its basis a private form of ownership of land, which is cultivated mainly by small and medium farms, and lease land relations are complemented by the market. And these relations, as in Poland, are regulated by state and self-governing bodies. It has been established that the latifundist model of the AL market is also based on private ownership of land, but the main market entities are not farms, but agricultural holdings. Within the framework of this model, land relations between the market entities are oriented mainly on land grabbing and are usually regulated by the general competence authorities. In general, this model is the most threatening to the food security of many countries where it is practiced, such as Madagascar, and the sustainable development of their rural areas. It is justified that the Ukrainian model of the AL market from July 21, 2021 to January 1, 2024 will have many signs of a farming model. But since then, it should not become a «hybrid» of the latifundist, but a combined version of the farm and state models. At the same time, the emphasis should be placed not on the privatization of land, but on their effective use, based on the advantages of the lease form of the land circulation, which are associated with the introduction of long-term lease, increasing its price and transferring to the electronic form.

Different functional feeding groups of mangrove soil molluscs invoke unique co‐occurrence patterns in response to a climate extreme

AbstractAimDue to differences in community functional traits and composition, the response of communities to environmental changes can be variable, and thus an understanding of the mechanisms underlying differential functional group responses is necessary. We investigated a mangrove soil mollusc community before (in 2007) and after (in 2008 and 2009) an extreme cold event (ECE) to determine the effects of the ECE on co‐occurrence patterns, spatiotemporal turnover and ecological processes in different functional groups (i.e. in‐faunal shelled deposit feeders [ISDFs] and hard‐bodied, mobile scavenger/predators [MS/Ps]).LocationSoutheast coasts of China.MethodWe used network analysis and null models to test the co‐occurrence patterns of the soil mollusc community. We used the analysis of distance and time decay to characterize the spatial turnover and temporal succession of the mollusc community based on presence/absence, relative abundance and biomass data. We performed random forest (RF), variation partitioning analysis (VPA) and Mantel tests to detect the effects of local environmental filtering and dispersal limitations on the soil mollusc community.ResultsWe found a decrease in species richness and biomass and an increase in abundance after an ECE, reflecting a significant change in mangrove soil mollusc communities. The network modularization, divergent succession and geographical differentiation of the ISDFs increased from 2008 to 2009, but environmental filtering and regional dispersal limitations decreased. The temporal trends of the network modules, geographical differentiation and dispersal limitations of MS/Ps followed a hump‐shaped pattern from 2008 to 2009, whereas the temporal trends of environmental filtering and temporal divergence exhibited an inverted hump‐shape pattern. The ECE changed the main environmental drivers of ISDFs and MS/Ps from water salinity to meteorology and vegetation factors.Main conclusionsMangrove soil mollusc communities in different functional groups invoked different spatiotemporal turnover models and ecological processes to shape unique co‐occurrence patterns in response to an ECE. We highlight the value of dividing different functional groups in developing predictive frameworks for a better understanding of community functional responses to global change.

A semimechanistic population pharmacokinetic and pharmacodynamic model incorporating autoinduction for the dose justification of TAS-114.

TAS‐114 is a dual deoxyuridine triphosphatase (dUTPase) and dihydropyrimidine dehydrogenase (DPD) inhibitor expected to widen the therapeutic index of capecitabine. Its maximum tolerated dose (MTD) was determined from a safety perspective in a combination study with capecitabine; however, its inhibitory effects on DPD activity were not assessed in the study. The dose justification to select its MTD as the recommended dose in terms of DPD inhibition has been required, but the autoinduction profile of TAS‐114 made it difficult. To this end, an approach using a population pharmacokinetic (PPK)/pharmacodynamic (PD) model incorporating autoinduction was planned; however, the utility of this approach in the dose justification has not been reported. Thus, the aim of this study was to demonstrate the utility of a PPK/PD model incorporating autoinduction in the dose justification via a case study of TAS‐114. Plasma concentrations of TAS‐114 from 185 subjects and those of the endogenous DPD substrate uracil from 24 subjects were used. A two‐compartment model with first‐order absorption with lag time and an enzyme turnover model were selected for the pharmacokinetic (PK) model. Moreover, an indirect response model was selected for the PD model to capture the changes in plasma uracil concentrations. Model‐based simulations provided the dose justification that DPD inhibition by TAS‐114 reached a plateau level at the MTD, whereas exposures of TAS‐114 increased dose dependently. Thus, the utility of a PPK/PD model incorporating autoinduction in the dose justification was demonstrated via this case study of TAS‐114.

A Novel Classification Model for Employees Turnover Using Neural Network to Enhance Job Satisfaction in Organizations

The most important challenge facing modern organizations is to keep their employees as valuable assists. Employee turnover is one of these challenges. This paper aims to develop a novel model that can help decision-makers to classify the problem of Employee Turnover. The proposed model is based on machine learning algorithms. The model was trained and tested by using a dataset that consists of 1470 records and 25 features. To develop the research model, many experiments had been conducted to find the best one. Based on implementation results, the Neural Network algorithm is selected as the best one with an Accuracy of 84% and AUC (ROC) of 74%. By validation mechanism, the model is acceptable and reliable to help origination decision-makers to manage their employees in a good manner and setting proactive plans to keep them. Besides the model, three important features should be dealt with carefully as Over Time, Job Level, Monthly Income.

Interrogation of Dystrophin and Dystroglycan Complex Protein Turnover After Exon Skipping Therapy.

Recently, the Food and Drug Administration granted accelerated approvals for four exon skipping therapies –Eteplirsen, Golodirsen, Viltolarsen, and Casimersen –for Duchenne Muscular Dystrophy (DMD). However, these treatments have only demonstrated variable and largely sub-therapeutic levels of restored dystrophin protein in DMD patients, limiting their clinical impact. To better understand variable protein expression and the behavior of truncated dystrophin protein in vivo, we assessed turnover dynamics of restored dystrophin and dystrophin glycoprotein complex (DGC) proteins in mdx mice after exon skipping therapy, compared to those dynamics in wild type mice, using a targeted, highly-reproducible and sensitive, in vivo stable isotope labeling mass spectrometry approach in multiple muscle tissues. Through statistical modeling, we found that restored dystrophin protein exhibited altered stability and slower turnover in treated mdx muscle compared with that in wild type muscle (∼44 d vs. ∼24 d, respectively). Assessment of mRNA transcript stability (quantitative real-time PCR, droplet digital PCR) and dystrophin protein expression (capillary gel electrophoresis, immunofluorescence) support our dystrophin protein turnover measurements and modeling. Further, we assessed pathology-induced muscle fiber turnover through bromodeoxyuridine (BrdU) labeling to model dystrophin and DGC protein turnover in the context of persistent fiber degeneration. Our findings reveal sequestration of restored dystrophin protein after exon skipping therapy in mdx muscle leading to a significant extension of its half-life compared to the dynamics of full-length dystrophin in normal muscle. In contrast, DGC proteins show constant turnover attributable to myofiber degeneration and dysregulation of the extracellular matrix (ECM) in dystrophic muscle. Based on our results, we demonstrate the use of targeted mass spectrometry to evaluate the suitability and functionality of restored dystrophin isoforms in the context of disease and propose its use to optimize alternative gene correction strategies in development for DMD.

Vicarious abusive supervision and turnover in expectant working mothers: Does financial dependency trigger emotional disconnect?

SummaryUsing a sample of 297 working mothers across three time periods (their last trimester of pregnancy, while on maternity leave, and after returning to the workplace), we examined the role of vicarious abusive supervision, beyond their own experience of abusive supervision, on turnover intentions through experiences of maternal mental health. Utilizing the unfolding model of turnover and Conservation of Resources theory, we found that experiencing the shock event of vicarious abusive supervision contributed to job‐related negative emotions as well as postpartum depressive symptoms in working new moms. Further, this experience of vicarious abusive supervision contributed to job‐related emotional exhaustion and turnover intentions, even after controlling for the mother's own experience of being targeted with abusive supervision behaviors. Finally, we examined the moderating role of financial dependence on this process and found that when working mothers' families were financially dependent on her job, the mothers were less likely to have turnover intentions. Implications for research and practice are provided.

Fluvial organic carbon cycling regulated by sediment transit time and mineral protection

Rivers transfer terrestrial organic carbon (OC) from mountains to ocean basins, playing a key role in the global carbon cycle. During fluvial transit, OC may be oxidized and emitted to the atmosphere as CO2 or preserved and transported to downstream depositional sinks. The balance between oxidation and preservation determines the amount of particulate OC (POC) that can be buried long term, but the factors regulating this balance are poorly constrained. Here, we quantify the effects of fluvial transit on POC fluxes along an ~1,300 km lowland channel with no tributaries. We show that sediment transit time and mineral protection regulate the magnitude and rate of POC oxidation, respectively. Using a simple turnover model, we estimate that annual POC oxidation is a small percentage of the POC delivered to the river. Modelling shows that lateral erosion into POC-rich floodplains can increase POC fluxes to downstream basins, thereby offsetting POC oxidation. Consequently, rivers with high channel mobility can enhance CO2 drawdown while management practices that stabilize river channels may reduce the potential for CO2 drawdown.

Turnback Intention: An Analysis of the Drivers of IT Professionals’ Intentions to Return to a Former Employer

Recent statistics indicate that most organizations prefer to fill IT vacancies by rehiring IT professionals who previously worked in the organization. Less is known about what drives IT professionals to “turnback,” a term we define as returning to employment with a former employer. To explain this important and rarely considered IT job mobility behavior, we build on job embeddedness theory and on the concepts of shocks and job dissatisfaction from, among others, the unfolding model of voluntary turnover to develop the theory of IT professional turnback. We perform fuzzy-set qualitative comparative analysis (fsQCA) of data collected from 248 IT professionals to draw conclusions about the intention among IT professionals to return to work for a former employer, and develop a midrange theory. Our results reveal two configurations contributing to high turnback intention and three configurations contributing to low turnback intention. Our model distinguishes between work shocks, personal shocks, and IT work shocks. IT shocks are a new category of shocks specific to the IT profession. We contribute theoretically by theorizing a behavior relevant to IT professionals and explaining attributes driving turnback intention.

Pharmacokinetic/Pharmacodynamic Modelling of Allopurinol, its Active Metabolite Oxypurinol, and Biomarkers Hypoxanthine, Xanthine and Uric Acid in Hypoxic-Ischemic Encephalopathy Neonates.

BackgroundAllopurinol, an xanthine oxidase (XO) inhibitor, is a promising intervention that may provide neuroprotection for neonates with hypoxic-ischemic encephalopathy (HIE). Currently, a double-blind, placebo-controlled study (ALBINO, NCT03162653) is investigating the neuroprotective effect of allopurinol in HIE neonates.ObjectiveThe aim of the current study was to establish the pharmacokinetics (PK) of allopurinol and oxypurinol, and the pharmacodynamics (PD) of both compounds on hypoxanthine, xanthine, and uric acid in HIE neonates. The dosage used and the effect of allopurinol in this population, either or not undergoing therapeutic hypothermia (TH), were evaluated.MethodsForty-six neonates from the ALBINO study and two historical clinical studies were included. All doses were administered on the first day of life. In the ALBINO study (n = 20), neonates received a first dose of allopurinol 20 mg/kg, and, in the case of TH (n = 13), a second dose of allopurinol 10 mg/kg. In the historical cohorts (n = 26), neonates (all without TH) received two doses of allopurinol 20 mg/kg in total. Allopurinol and oxypurinol population PK, and their effects on inhibiting conversions of hypoxanthine and xanthine to uric acid, were assessed using nonlinear mixed-effects modelling.ResultsAllopurinol and oxypurinol PK were described by two sequential one-compartment models with an autoinhibition effect on allopurinol metabolism by oxypurinol. For allopurinol, clearance (CL) was 0.83 L/h (95% confidence interval [CI] 0.62–1.09) and volume of distribution (Vd) was 2.43 L (95% CI 2.25–2.63). For metabolite oxypurinol, CL and Vd relative to a formation fraction (fm) were 0.26 L/h (95% CI 0.23–0.3) and 11 L (95% CI 9.9–12.2), respectively. No difference in allopurinol and oxypurinol CL was found between TH and non-TH patients. The effect of allopurinol and oxypurinol on XO inhibition was described by a turnover model of hypoxanthine with sequential metabolites xanthine and uric acid. The combined allopurinol and oxypurinol concentration at the half-maximal XO inhibition was 0.36 mg/L (95% CI 0.31–0.42).ConclusionThe PK and PD of allopurinol, oxypurinol, hypoxanthine, xanthine, and uric acid in neonates with HIE were described. The dosing regimen applied in the ALBINO trial leads to the targeted XO inhibition in neonates treated with or without TH.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40262-021-01068-0.

Global scenarios of residential heating and cooling energy demand and CO2 emissions

Buildings account for 36% of global final energy demand and are key to mitigating climate change. Assessing the evolution of the global building stock and its energy demand is critical to support mitigation strategies. However, most global studies lack granularity and overlook heterogeneity in the building sector, limiting the evaluation of demand transformation scenarios. We develop global residential building scenarios along the shared socio-economic pathways (SSPs) 1–3 and assess the evolution of building stock, energy demand, and CO2 emissions for space heating and cooling with MESSAGEix-Buildings, a modelling framework soft-linked to an integrated assessment framework. MESSAGEix-Buildings combines bottom-up modelling of energy demand, stock turnover, and discrete choice modelling for energy efficiency decisions, and accounts for heterogeneity in geographical contexts, socio-economics, and buildings characteristics.Global CO2 emissions for space heating are projected to decrease between 34.4 (SSP3) and 52.5% (SSP1) by 2050 under energy efficiency improvements and electrification. Space cooling demand starkly rises in developing countries, with CO2 emissions increasing globally by 58.2 (SSP1) to 85.2% (SSP3) by 2050. Scenarios substantially differ in the uptake of energy efficient new construction and renovations, generally higher for single-family homes, and in space cooling patterns across income levels and locations, with most of the demand in the global south driven by medium- and high-income urban households. This study contributes an advancement in the granularity of building sector knowledge to be assessed in integration with other sources of emissions in the context of global climate change mitigation and sustainable development.

JUMPt: Comprehensive Protein Turnover Modeling of In Vivo Pulse SILAC Data by Ordinary Differential Equations.

Recent advances in mass spectrometry (MS)-based proteomics allow the measurement of turnover rates of thousands of proteins using dynamic labeling methods, such as pulse stable isotope labeling by amino acids in cell culture (pSILAC). However, when applying the pSILAC strategy to multicellular animals (e.g., mice), the labeling process is significantly delayed by native amino acids recycled from protein degradation in vivo, raising a challenge of defining accurate protein turnover rates. Here, we report JUMPt, a software package using a novel ordinary differential equation (ODE)-based mathematical model to determine reliable rates of protein degradation. The uniqueness of JUMPt is to consider amino acid recycling and fit the kinetics of the labeling amino acid (e.g., Lys) and whole proteome simultaneously to derive half-lives of individual proteins. Multiple settings in the software are designed to enable simple to comprehensive data inputs for precise analysis of half-lives with flexibility. We examined the software by studying the turnover of thousands of proteins in the pSILAC brain and liver tissues. The results were largely consistent with the proteome turnover measurements from previous studies. The long-lived proteins are enriched in the integral membrane, myelin sheath, and mitochondrion in the brain. In summary, the ODE-based JUMPt software is an effective proteomics tool for analyzing large-scale protein turnover, and the software is publicly available on GitHub (https://github.com/JUMPSuite/JUMPt) to the research community.

Fibrillar Collagen: A Review of the Mechanical Modeling of Strain-Mediated Enzymatic Turnover

AbstractCollagen is the most abundant protein in mammals, often serving as the main load bearing constituent in soft tissues. Collagen undergoes continuous remodeling processes in which present collagen degrades, and new collagen is formed and deposited. Experiments find that modestly strained fibrillar collagen is often stabilized to enzymatic degradation, a mechanism that is essential in approaching and maintaining a homeostatic balance in the tissue remodeling process for healthy tissue. At larger strains, this decline in the collagen degradation rate may be reversed. This article reviews different modeling approaches that seek to account for the effect of straining on collagen remodeling, both with respect to collagen amount and to resulting mechanical properties. These models differ in the considered length scale starting from the molecular scale up to the larger continuum scale.

Species composition and turnover models provide robust approximations of biodiversity in marine conservation planning

Robust design of Marine Protected Areas in ocean environments is often challenging due to inadequate knowledge of biodiversity patterns, reflecting difficulties in the prediction of species distributions from sampling data that are often sparse or inadequate. Models that combine species and environmental data, such as Gradient Forests (GF), provide one analytical approach to this problem, efficiently combining available information to produce spatial models of species turnover throughout an area of interest. Spatial estimates of species turnover can then be classified to estimate spatial patterns in species composition; however, the performance of GF-based classifications within a conservation planning context has not previously been evaluated. Here we assess the utility for conservation planning (using the software Zonation) of a GF-based hierarchical classification that summarises spatial patterns in demersal fish composition in the oceans around New Zealand. Progressively more complex Zonation analyses assessed the effects of (i) varying the number of classification groups, (ii) adding information describing species turnover, and (iii) adding information describing spatial variation in demersal fish species richness. The best-performing GF-based conservation ranking used layers describing the distributions of 30 classification groups, demersal fish species turnover between these groups, and species richness. Conservation outcomes from this ranking were only marginally less efficient than those from a more conventional ranking that used 217 individual species distribution layers (7% less efficient). This indicates that GF-based classifications may provide a practical alternative for marine conservation planning. Additional advantages arise from the greater ease with which a single classification layer summarising complex biodiversity patterns can facilitate decision-making in participatory stakeholder processes.

Here today, gone tomorrow: A mixed-method study on headhunter-intermediated recruitment practices

While unsolicited job offers are the strongest pull factor driving turnover, little is known about headhunters’ candidate contacts and outcomes. Drawing on the unfolding model of voluntary turnover (Lee & Mitchell, 1994) and research on headhunters, this study examines what kind of employees are contacted by headhunters and why some of them leave. Using the case of Japan, where subsidiaries of foreign multinational corporations use extensively headhunters to recruit host country national employees (HCNs), we first conducted interviews with 131 expatriate managers (clients), contingency-based headhunters, and HCN employees (candidates). The findings suggest that headhunters’ contacts were guided by HCNs’ English proficiency, tenure, and previous placement by headhunters. The findings also suggest that headhunters’ contacts can drive up turnover. To further examine the antecedents and outcomes of headhunter contacts, we collected time-lagged survey data from 456 HCN employees in foreign subsidiaries. In addition to confirming our interview findings, the survey findings also suggest that headhunters’ contacts have a positive relationship with HCN employees’ voluntary turnover.

A Theoretical Model of Executive Voluntary Turnover

For the current organizations, retaining executive members is one of the most important functions of human resource management. Given that importance, although executives’ mobility becomes prevalent, most prior studies tended to focus on involuntary turnover of executive members. To fill this gap, the current theoretical paper suggests a model of executive voluntary turnover, drawing on the lierature of employee mobility and entrepreneurship. First, running a new business as a CEO negatively affects prior-firm performance, but collaboration between two firms mitigate the negative association. Second, spin-off positively affects prior-firm performance, but this is weakened as spin-off firm performance decreases. Finally, moving to a competitor negatively, while moving to a collaborator positively affects prior-firm performance.

Determinant Factors of Labor Turnover- A New Perspective

Purpose: The study aims to develop a conceptual framework based on the existing labor turnover model and test it empirically. The model tested how dissatisfaction with government rules and regulations, work environment, social environment, and shock to the system and demographic factors impact turnover.
 Design/Methodology/Approach: This is a cross-sectional study conducted based on data collected from 384 employees who have left the garment industry in Sri Lanka. Data were analyzed through Analysis of Variance (ANOVA) and Multiple Regression Analysis.
 Findings: The results indicate dissatisfaction with government rules and regulations, work environment, social environment, a shock to the system, age, service, and income significantly influence labor turnover. 
 Research Limitations/Implications: The scope of this study did not cover factors that can affect employees' turnover, such as dissatisfaction with low performance, voice, and neglect of work, high absenteeism, and grievances. 
 Practical Implications: Policy-makers can use the tested model to determine the causes of the existing issue of labor turnover and intervene to formulate strategies/policies, devise solutions for the same. Management intervention would be effective to help handle and minimize problems associated with the existing issue of labor turnover.
 Originality/Value: To date, previous studies are based on the existing employees' intention to quit. However, the present study considers employees who have already quit the industry; thus, the study fills the empirical gap in the area of research on labor turnover.