Job Crafting and Employees’ Performance in MTN Nigeria PLC

This study examines the relationship between job crafting (task crafting and relational crafting) and employees' performance (employees’ task performance and organizational citizen behavior) amongst staff of MTN Nigeria PLC. This research makes use of a survey design and analysis was based on primary data generated through a structured questionnaire. Two research hypotheses were formulated and tested at 0.05 levels of significance. The findings revealed that there was a statistically significant influence of task crafting on employees’ task performance in MTN Nigeria, PLC (R2=0.088, F=17.844, p<0.050). Similarly, there is a significant positive relationship between relational crafting and organizational citizenship behavior (rp=0.331, n=187, p<0.050). From the study, it was concluded that workers require a high degree of autonomy and independence on their jobs to perform more efficiently and effectively in order to improve their performance. It was recommended amongst others that organization should provide a flexible job design and structure as well as interpersonal relationship for its employees’ so as to enable them to better perform on the task and create organizational citizen behavior among the employees. Keywords: employees’ performance, job crafting, relational crafting, organizational citizen behavior

Rethinking neglected tropical disease prevalence survey design and analysis: a geospatial paradigm

Current methods for the design and analysis of neglected tropical disease prevalence surveys largely rely on classical survey sampling ideas that treat prevalence data from different locations as an independent random sample from the probability distribution induced by a random sampling design. We set out an alternative, explicitly geospatial paradigm that can deliver much more precise estimates of the geospatial variation in prevalence over a country or region of interest. We describe the advantages of this approach under three headings: streamlining, whereby more precise results can be obtained with smaller sample sizes; integrating, whereby a joint analysis of data from two or more diseases can bring further gains in precision; and adapting, whereby the choice of future sampling location is informed by past data.

Job Crafting and Employees’ Performance in MTN Nigeria, Plc

This study examines the relationship between job crafting (task crafting and relational crafting) and employees’ performance (employees’ task performance and organizational citizen behaviour) amongst staff of MTN Nigeria Plc. This research makes use of a survey design and analysis was based on primary data generated through a structured questionnaire. Two research hypotheses were formulated and tested at 0.05 level of significance. The findings revealed that there was a statistically significant influence of task crafting on employees’ task performance in MTN Nigeria, Plc (R2 = .088, F = 17.844, p < 0.050). Similarly, there is a significant positive relationship between relational crafting and organizational citizen behaviour ( rp=0.331, n=187, p < 0.050). From the study, it was concluded that workers require a high degree of autonomy and independence on their jobs to perform more efficiently and effectively in order to improve their performance. It was recommended amongst others that organization should provide a flexible job design and structure as well as interpersonal relationship for its employees’ so as to enable them to better perform on the task and create organizational citizen behavior among the employees.

Design and Analysis of Elimination Surveys for Neglected Tropical Diseases

As neglected tropical diseases approach elimination status, there is a need to develop efficient sampling strategies for confirmation (or not) that elimination criteria have been met. This is an inherently difficult task because the relative precision of a prevalence estimate deteriorates as prevalence decreases, and classic survey sampling strategies based on random sampling therefore require increasingly large sample sizes. More efficient strategies for survey design and analysis can be obtained by exploiting any spatial correlation in prevalence within a model-based geostatistics framework. This framework can be used for constructing predictive probability maps that can inform in-country decision makers of the likelihood that their elimination target has been met, and where to invest in additional sampling. We evaluated our methodology using a case study of lymphatic filariasis in Ghana, demonstrating that a geostatistical approach outperforms approaches currently used to determine an evaluation unit’s elimination status.

A Survey, Design and Analysis of IoT Security and QoS Challenges

IoT is a technological exemplar with a vision of “Everything is connected” enabling everyone to publish their generated data collected from different heterogeneous and homogenous systems onto the web. The basic concept of IoT is connectivity, a set of physical objects that use network support to exchange data. These objects can be software, boards, sensors, etc. In the real end to end network deployment, IoT is a platform and cloud is one part of it. In order to turn the IoT vision into reality high reliability, security and QoS are required to support the communications between the homogenous and heterogeneous networks. The security and QoS are critical factors in the real End to End topology. In this article, the authors proposed the various challenges for IoT security, and IoT routing between the edge and cloud.

SKDA in Context

In contrast to the view that survey key driver analysis (SKDA) is a misused and blind empirical process, we suggest it is a reasonable, hypothesis-driven approach that builds on cumulative knowledge drawn from both the literature and practice, and requires reasoned judgment about the relationships of individual items to the constructs they represent and the criteria of interest. The logic of key driver analysis in applied settings is no different than the logic of its application in fundamental research regarding employee attitudes (e.g., Dalal, Baysinger, Brummel, & LeBreton, 2012). However, there are important survey design and analysis issues with respect to how key driver analyses are best conducted. Just some of these are discussed below.