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\title{Impact of Continuous Learning Culture and Employee Self Efficacy on Training Effectiveness: Empirical Evidence from Insurance Sector in India}
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             \author[1]{Pooja  Sharma}

             \author[2]{Richa  Sharma}

             \affil[1]{  Jiwaji University, Gwalior}

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\date{\small \em Received: 13 December 2015 Accepted: 1 January 2016 Published: 15 January 2016}

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\begin{abstract}
        


In today?s competitive global era, organizations need to retain efficient and competent employees who perform excellent work in a congenial environment. The purpose of the research is to examine the positive and significant impact of continuous learning culture and self efficacy on training effectiveness in the context of insurance sector. Three variables were being examined, continuous learning culture and self efficacy as an independent variable and training effectiveness as a dependent variable. For this purpose data was collected from two hundred employees from various two insurance companies in India especially Delhi through questionnaires. Data from target respondents was analyzed in the form of reliability analysis. Linear and multiple regression were applied to find the impact of independent variables on dependent variable. Findings of the study revealed that continuous learning culture and self efficacy have a positive and significant impact on training effectiveness.

\end{abstract}


\keywords{continuous learning culture, insurance sector, self efficacy and training effectiveness.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
ndia is a developing country and it has the capability to become a strong nation with its huge natural, technological and human resources. In this era of stiff competition, rapidly changing the needs and preferences of customer, only a learning organization can stay ahead. In developing the human resource and instilling a culture of learning in an organization, training plays a crucial role in deciding the competitive edge of an organization over the market players. Training is inevitable function of an organization as it develops the skills and knowledge of an employee, enables them to take up challenging tasks and assist the organization to compete the today's rapidly changing situations of business. 
\section[{a) Continuous Learning Culture}]{a) Continuous Learning Culture}\par
Systematic training enables an opportunity for learning and these learning processes depends upon Author ? ?: UGC-NET senior Research Fellow, Jiwaji University, Gwalior, Madhya Pradesh, India Mailing address: 07, aliza bagh, shinde ki chhawani, lashkar, Gwalior, Madhya Pradesh, India. e-mails: smileypoojasharma90@gmail.com, rich\textunderscore sharma29@yahoo.co.in many factors such as the design of the training programme, learning style of the trainees and the learning environment of the organization. As organizations struggle to survive in an increasingly competitive environment, Continuous knowledge acquisition potentially leads to increased productivity and help organizations to remain effective and competitive. 
\section[{b) Self efficacy}]{b) Self efficacy}\par
Self-efficacy is an individual's general belief, that they are able to change their performance when desired. It is the people's judgment of their capabilities to organize and execute courses of action, required to attain designated types of performance. 
\section[{c) Training effectiveness}]{c) Training effectiveness}\par
Training effectiveness is evaluated by measuring a number of training and transfer results. It basically deals with how trainees are applying newly acquired skills from training to the job or behaviour that is retained and applied in the workplace. 
\section[{d) Insurance sector}]{d) Insurance sector}\par
In the current scenario insurance sector has become a challenging field which is full of exciting tasks for the employees. Life Insurance Corporation (LIC) is the sole public sector company in life insurance business and General Insurance Corporation of India is a public sector non life insurance company.\par
i.  \hyperref[b12]{(David Pollitt, 2009)} stated the significance of training to customer facing staff of AXA sun life insurance sector. He said that in a fiercely competitive, tightly regulated insurance sector, a customer-facing staff must be trained to fairly sell the right product at the right time. \hyperref[b3]{(Cody Cox. B, 2009)} examined the moderating effect of individual differences in the relationship between framing training for technical and nontechnical content areas. Self-efficacy and goal orientation were examined as moderators. Result indicated that there was a threeway interaction between performance orientation, age, and frame for technical training and a three-way interaction between performance orientation, selfefficacy, and frame for nontechnical training. (Ramachandran, 2010) studied the effectiveness of training programme of different cadre of employees, working in a public sector organization and suggested that employees were differed in effectiveness of training programme on the basis of demographic characters. \hyperref[b2]{(Canning, 2011)} suggested that the organizations should develop working groups where younger workers can learn the knowledge and skills from older employees and benefitted by the experiences of them. So that experiences of older employees should be valued. When an individual willingly learn new skills then the individual takes the "education initiative" \hyperref[b17]{(Warr \& Fay 2001)}. \hyperref[b14]{(Sessa and London, 2006)} proposed three approaches, through which individuals can learn. These approaches are: adaptation, generation and transformation. In adaptation approach an employee can learn by continuously adapting to changes in the environment. This learning is unintentional and unintended. Through generation, an Individual can learn by generating new knowledge and conditions. In transformation learning encourages reflection and result in transfer of knowledge from learning to work. \hyperref[b10]{(Maurer, Weiss and Barbeite, 2003)} found that the perceived intrinsic benefits like career planning was the key predictor of an individual's willingness to participate in a learning activity. \hyperref[b6]{(Hinds et al., 2001}) revealed some differences which were shown by experts and beginners in a way of communication during training program. He stated that matching the skill levels of the trainer and the trainee increase the likelihood that the trainees can learn.\par
IV. 
\section[{Rationale of the Study}]{Rationale of the Study}\par
Present study reports the empirical results of a study designed to examine the impact of certain variables on training effectiveness and highlights the significance of training activities. Broadly the research seeks to enlighten the public insurance sector enterprises specifically the LIC of India with the knowledge and experience to expand the horizon of training practices for a sustainable organizational development.\par
But, the research gap that we found by the study of aforementioned literature is that, there is no indepth study was conducted in insurance sector for measuring the outcomes through training practices. This study is expected to provide some insights in that area, and fill an important knowledge gap. Hence this study is rationale for measuring the impact of all the independent variables (continuous learning culture and self efficacy) on the dependent variable (training effectiveness.) Indian insurance sector.\par
V. 
\section[{Hypothesis}]{Hypothesis}\par
Based on the above discussions and supports from the preceding works, the following hypothesis was established for this study: H 1 : There is positive and significant impact of continuous learning culture on training effectiveness.\par
H 2 : There is positive and significant impact of self efficacy on training effectiveness. H 03 : There is no significant combined impact of both the independent variables (continuous learning culture and self efficacy) on training effectiveness. 
\section[{PROPOSED MODEL}]{PROPOSED MODEL} 
\section[{Independent variables}]{Independent variables}\par
Dependent variable The responses taken on the Likert type of 1 to 5 where 1 represent strongly disagree and 5 represent the strongly agree. Total responses were elicited on 30 items, which took 15 minutes to answer. 
\section[{c) Measurement}]{c) Measurement}\par
? Self-efficacy. An eight-item scale to measure selfefficacy was drawn from previous research \hyperref[b8]{(Jones, 1986}).\par
? Continuous learning culture is assessed using a ten items scale taken from Tracy et al.,  {\ref (1995)}.\par
? the above table it can be concluded that the value of Cronbach Alpha for all the three variables is more than 0.7. Therefore it could be used in this study. 
\section[{b) Linear regression}]{b) Linear regression}\par
The regression table provides the result of constant, coefficient of determination, t-value.\par
Coefficient is the slope of regression line and it explains that 1 unit change in independent Variable will bring how much change in dependent variable. The coefficient of determination (R 2 ) explains how much variation in the dependent variable is explained by the independent variable. 
\section[{i. Linear regression values for continuous learning culture as independent variable and training effectiveness as dependent variable}]{i. Linear regression values for continuous learning culture as independent variable and training effectiveness as dependent variable}\par
The regression results interpret the value of coefficient .729 that indicates 1\% change in independent variable (continuous learning culture) can result in 72.9\% change in dependent variable (Training effectiveness). This relationship is positive and significant as shown by small p value.   The regression results interpret the value coefficient .809 that indicates 1\% change in independent variable (self efficacy) can result in 80.9\% change in dependent variable (training effectiveness). Thus, if self efficacy is increased by 1\%, this will result in 80.9\% increase in effectiveness. This relationship is positive and significant as shown by small p value. Thus supporting H 2 , that self efficacy has positive impact on training effectiveness.  So we can conclude that there is significant combined impact of continuous learning culture and self efficacy on training effectiveness. Hence null hypothesis of our study has been rejected. 
\section[{ii. Linear regression values for self efficacy as independent variable and training effectiveness as dependent variable:}]{ii. Linear regression values for self efficacy as independent variable and training effectiveness as dependent variable:} 
\section[{iii. Multiple regression values for continuous learning culture and self efficacy as independent variables and training effectiveness as dependent variable}]{iii. Multiple regression values for continuous learning culture and self efficacy as independent variables and training effectiveness as dependent variable} 
\section[{Implications of Study}]{Implications of Study}\par
The results of this study have contributed to the body of knowledge in the field of individual characteristics (self efficacy) in the insurance sector of India. Our study discovered the positive and noteworthy association between training and effectiveness. Theoretically speaking, findings of the study revealed a significant relationship between continuous learning culture, self efficacy and transfer of training. There are few practical indications that we can draw from this study for academician, researchers and various service industries. For researchers, it acts as a knowledge base for further studies related with this topic. For service industry the result will provide a great help in developing a learning culture where employees conveniently learn new knowledge and skills related their task. It provides guidelines to enhance self efficacy of employees. 
\section[{IX.}]{IX.} 
\section[{Limitations of the Study}]{Limitations of the Study}\par
This study has some limitations, firstly this study examined relationship between continuous learning culture and training effectiveness, and it took only some dimensions under each variable. Secondly the study was done on few cities of India, all cities were not covered in it, and so the generalization of the results and findings are not warranted. Thirdly, the data was collected within a period of time, so the findings are confined for a particular period and cannot be generalized for longer period of time. Fourthly, we applied multiple regressions but if other measurement versions were used, then the result would be different. 
\section[{X.}]{X.} 
\section[{Future research}]{Future research}\par
Firstly, future work can overcome limitations of the present study in terms of number of respondents and focusing on the whole state that will help in generalizing the findings of the study. Secondly, future research can look for other moderating and mediating variables that can affect the relationship between continuous learning culture, self efficacy and training effectiveness. Other variables may be considered like supervisory support and motivation to learn for examining the effectiveness of training. 
\section[{XI.}]{XI.} 
\section[{CONCLUSION}]{CONCLUSION}\par
In today's global dynamic era organizations are forced to function effectively in changing situations and under various complications, and it is crucial for companies to have the qualified employees at the right job at the right time in order to survive the surrounding competition. So that training is considered as a fundamental and effectual instrument in accomplishment of the firm's objectives. Training is a performance development process to foster learning new techniques and methods to perform job with fullest efficiency and effectiveness. Training builds and strengthens relationships with and among workplace partners and better engage employers, unions to respond to the challenges of workplace.\begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.8195956454121306\textwidth}P{0.030404354587869362\textwidth}}
\multicolumn{2}{l}{d) Tools Used for data Analysis: Cronbach alpha was}\\
\multicolumn{2}{l}{applied to assess reliability and the relationship}\\
\multicolumn{2}{l}{between the variables was established through}\\
\multicolumn{2}{l}{linear and multiple Regression.}\\
VII.\tabcellsep Results and Discussions\\
\multicolumn{2}{l}{a) Reliability: Reliability reflects the consistence of a set}\\
\multicolumn{2}{l}{of items variables scale by measuring the concept}\\
\multicolumn{2}{l}{in a particular. In this study, reliability measurement}\\
\multicolumn{2}{l}{is important to verify the variables consistencies}\\
\multicolumn{2}{l}{through continuous learning culture, self efficacy}\\
\multicolumn{2}{l}{and training effectiveness. Cronbach's alpha is}\\
\multicolumn{2}{l}{computed using SPSS scale reliability programme}\\
\multicolumn{2}{l}{for each set of constructs. The value of Cronbach's}\\
\multicolumn{2}{l}{alpha is reported in Table 1.}\end{longtable} \par
  {\small\itshape [Note: Training Effectiveness: This will be measured with five item scale from xiao (1996) and six items from Galanou, E. \& Priporas, and C. V., (2009).]} 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.578310502283105\textwidth}P{0.021347031963470316\textwidth}P{0.03881278538812785\textwidth}P{0.06015981735159817\textwidth}P{0.034931506849315064\textwidth}P{0.07568493150684931\textwidth}P{0.009703196347031963\textwidth}P{0.03105022831050228\textwidth}}
Model\tabcellsep \tabcellsep \tabcellsep Std. Error\tabcellsep \tabcellsep \multicolumn{2}{l}{Change Statistics}\tabcellsep \\
\tabcellsep R\tabcellsep Adjusted\tabcellsep of the\tabcellsep R Square\tabcellsep F\tabcellsep \tabcellsep Sig. F\\
R\tabcellsep Square\tabcellsep R Square\tabcellsep Estimate\tabcellsep Change\tabcellsep \multicolumn{2}{l}{Change df1 df2}\tabcellsep Change\\
dimension0 1 .846 a\tabcellsep .628\tabcellsep .626\tabcellsep 8.58373\tabcellsep .628\tabcellsep 231.450\tabcellsep 1 198\tabcellsep .000\\
\multicolumn{4}{l}{a. Predictors: (Constant), continuous learning culture}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. Dependent Variable: training effectiveness}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{8}{l}{Model summary table indicates that value of coefficient of determination (R 2 ) is .628 reveals that continuous}\\
\multicolumn{4}{l}{learning culture accounts to 62.8\% variation in effectiveness.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.1964824120603015\textwidth}P{0.1708542713567839\textwidth}P{0.1623115577889447\textwidth}P{0.08115577889447236\textwidth}P{0.13668341708542714\textwidth}P{0.05125628140703517\textwidth}P{0.05125628140703517\textwidth}}
\tabcellsep Model\tabcellsep \tabcellsep \tabcellsep Standardized\tabcellsep \\
\tabcellsep \tabcellsep \multicolumn{2}{l}{Unstandardized Coefficients}\tabcellsep Coefficients\tabcellsep \\
\tabcellsep \tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\tabcellsep t\tabcellsep Sig.\\
1\tabcellsep (Constant)\tabcellsep 12.101\tabcellsep 2.175\tabcellsep \tabcellsep 4.547\tabcellsep .000\\
\tabcellsep Continuous\tabcellsep .602\tabcellsep .045\tabcellsep .729\tabcellsep 14.780\tabcellsep .000\\
\tabcellsep learning\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep culture\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent Variable: training effectiveness}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.17305389221556886\textwidth}P{0.02035928143712575\textwidth}P{0.10179640718562874\textwidth}P{0.15778443113772453\textwidth}P{0.09161676646706587\textwidth}P{0.19850299401197605\textwidth}P{0.025449101796407185\textwidth}P{0.081437125748503\textwidth}}
Model\tabcellsep \tabcellsep \tabcellsep Std. Error\tabcellsep \tabcellsep \multicolumn{2}{l}{Change Statistics}\tabcellsep \\
\tabcellsep \tabcellsep Adjusted R\tabcellsep of the\tabcellsep R Square\tabcellsep F\tabcellsep \tabcellsep Sig. F\\
\multicolumn{2}{l}{R R Square}\tabcellsep Square\tabcellsep Estimate\tabcellsep Change\tabcellsep \multicolumn{2}{l}{Change df1 df2}\tabcellsep Change\\
dimension0 1 .810 a\tabcellsep .684\tabcellsep .683\tabcellsep 7.35126\tabcellsep .684\tabcellsep 367.954\tabcellsep 1 198\tabcellsep .000\end{longtable} \par
  {\small\itshape [Note: a. Predictors: (Constant), self efficacy b. Dependent Variable: training effectiveness Model summary table indicates that value of coefficient of determination (R 2 ) is .684 reveals that self efficacy accounts to 68.4\% variation in training effectiveness.]} 
\caption{\label{tab_4}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.4009966777408638\textwidth}P{0.03106312292358804\textwidth}P{0.05647840531561462\textwidth}P{0.09036544850498339\textwidth}P{0.05083056478405316\textwidth}P{0.11013289036544849\textwidth}P{0.014119601328903655\textwidth}P{0.045182724252491695\textwidth}P{0.05083056478405316\textwidth}}
Model\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Change Statistics}\tabcellsep \tabcellsep \\
\tabcellsep R\tabcellsep Adjusted R\tabcellsep Std. Error of\tabcellsep R Square\tabcellsep F\tabcellsep \tabcellsep Sig. F\tabcellsep Durbin-\\
R\tabcellsep Square\tabcellsep Square\tabcellsep the Estimate\tabcellsep Change\tabcellsep \multicolumn{2}{l}{Change df1 df2}\tabcellsep Change\tabcellsep Watson\\
dimension0 1 .827 a\tabcellsep .656\tabcellsep .653\tabcellsep 6.84535\tabcellsep .656\tabcellsep 235.539\tabcellsep 2 197\tabcellsep .000\tabcellsep 1.548\\
\multicolumn{5}{l}{a. Predictors: (Constant), continuous learning culture and self efficacy}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. Dependent Variable: training effectiveness}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_5}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_6}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.2090909090909091\textwidth}P{0.12727272727272726\textwidth}P{0.17272727272727273\textwidth}P{0.08636363636363636\textwidth}P{0.14545454545454545\textwidth}P{0.05454545454545455\textwidth}P{0.05454545454545455\textwidth}}
\tabcellsep Model\tabcellsep \tabcellsep \tabcellsep Standardized\tabcellsep \\
\tabcellsep \tabcellsep \multicolumn{2}{l}{Unstandardized Coefficients}\tabcellsep Coefficients\tabcellsep \\
\tabcellsep \tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\tabcellsep T\tabcellsep Sig.\\
1\tabcellsep (Constant)\tabcellsep 8.226\tabcellsep 1.897\tabcellsep \tabcellsep 4.268\tabcellsep .000\\
\tabcellsep Self efficacy\tabcellsep 1.010\tabcellsep .045\tabcellsep .809\tabcellsep 19.264\tabcellsep .000\\
\multicolumn{3}{l}{a. Dependent Variable: training effectiveness}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 5 :}\end{figure}
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