The heart of survey research lies in the research instrument used. A questionnaire is one of the most widely used research instruments in management science research. However, its development has become a concern for researchers in management sciences. It has been observed that there are challenges in developing a questionnaire, as well as the steps involved. Based on this, the paper explored the development of instrumentation in management sciences research, with a questionnaire as the focus. The study adopted a qualitative research approach with interpretivism as the research paradigm. Content analysis was adopted due to the nature of the paper. The paper reported that questionnaire item development did not follow appropriate steps in most management science research. It was concluded that appropriate steps must be followed: The Conceptualization Stage, Items Generation Stage, Construction Stage, and Evaluation Stage (CICE). The paper therefore recommended that the Conceptualization Stage, Items Generation Stage, Construction Stage, and Evaluation Stage (CICE) be adopted when formulating a questionnaire for management sciences researchers. The questionnaire items should be developed in line with the variables adopted as measures of the construct of interest.
Health care data analytics is transforming the way medical services are delivered, managed, and improved. Every day, hospitals, clinics, laboratories, pharmacies, and wearable devices generate vast amounts of data that need to be transformed and analyzed. Thus, health care data analytics has become important for patients' wellbeing. The study developed and tested two direct and three moderating hypotheses. The study adopted a questionnaire from past studies using a five-point Likert scale. The sample size for the study was 350, which is appropriate for Smart PLS studies. We collected the data via a Google Form and focused on physicians and staff at the leading health care units in Karachi. We found support for all five articulated hypotheses. We accepted the Hypothesis stating that “IT infrastructure positively affects health care data analytics”. The result also supported the Hypothesis that health care policies positively affect healthcare data analytics. We accepted the hypothesis stating “data integration positively affects health care data analytics.” We found support for the hypothesis, which states “data integration positively affects healthcare data analytics. We also found support for the Hypothesis that states “Data growth maturity moderate IT infrastructure and health care data analytics." We also found support for the last hypothesis, which states “organizational culture moderate IT infrastructure and health care data analytics. All the accepted hypotheses align with prior studies and the literature.
The study has developed a theoretical framework, which has four hypotheses, two direct and two moderating. The study collected data using a five-point Likert-scale questionnaire adapted from prior studies. The sample size for the study was 260, and we collected data physically and from Google Forms. Before collecting the data, we followed all required ethical protocols. Four articulated hypotheses were tested and accepted. Hypothesis 1: “Risk-averse attitudes negatively affect entrepreneurial growth” was accepted. We accepted Hypothesis 2: “Absence of social capital negatively affects entrepreneurial growth. We accepted Hypothesis 3, “Exposure to entrepreneurial knowledge mediates the association between risk-averse attitudes and entrepreneurial growth. We accepted Hypothesis 4: “Exposure to entrepreneurial knowledge mediates the association between absence of social capital and entrepreneurial growth. The study has empirically tested the variables drawn from the Theory of Planned Behavior. Hence, enhancing its generalizability, as the authors of the theory have themselves admitted that their theory may face issues if applied in other cultures.
The banking sector plays an important role in countries’ economies and financial development. It operates in a highly competitive and technology-driven environment. Employee performance, customer satisfaction, and organizational performance are particularly important in this sector. The banking sector also employs a large workforce. Given its importance, we developed a conceptual framework that has one direct, two mediating, and two moderating relationships. The study adopted a quantitative approach, and the study’s sample size was 200. We used convenience sampling and adopted questionnaires from previous studies similar to this one. Using Smart PlS for data analysis, we found that one direct and two moderating relationships were supported. However, we did not find support for two mediating relationships. We accepted Hypothesis 1: GTL “positively affects GEE. Our results do not support Hypothesis 2: “GEB mediates the relationship between GTL and GEE.” We rejected Hypothesis 3: “GOCB mediates the relationship between GTL and GEE.” We accepted Hypothesis 4: “AIT moderates the relationship between GTL and GEE.” Our results supported Hypothesis 5: “AIL moderates the relationship between GTL and GEE.” The direct and moderating hypotheses results align with the past literature. However, the mediating hypothesis results do not align with the past studies.
Female entrepreneurs in developed and developing countries contribute significantly in generating household income. Despite this, they have several disadvantages compared to their male counterparts. They have to cope with the cultural and other barriers common in developing countries. Given these, we have developed a conceptual framework with one dependent variable (female entrepreneurship). Four predictors (i.e., Personal traits, institutional environment, government and NGOs assistance, and perceived access to finance) and three moderators (i.e., self-efficacy, family support, and financial literacy). We collected the data using a pre-developed questionnaire adopted from past studies. The target population for this study was female entrepreneurs in urban cities. The study sample size was 325, and we collected data both in person and online. The study used Smart PLS for data analysis. All the articulated hypotheses were approved. We accepted Hypothesis 1:“ Personal support positively affects female entrepreneurial activity. The results support Hypothesis 2:” Institutional environment positively affects female entrepreneurial activity. The results support Hypothesis 3: “Government NGO assistance positively affects female entrepreneurial activity, We accepted Hypothesis 4: “Perceived access to finance positively affects female entrepreneurial activity. The results support Hypothesis 5: “Self-efficacy moderates the relationship between personal traits and female entrepreneurial activity. The results support Hypothesis 6: “Financial support moderates the relationship between personal traits and female entrepreneurial activity. We accepted Hypothesis 7: “Financial literacy moderates the relationship between Government and NGO assistance and female entrepreneurial activity.
