RESEARCH ARTICLES

 

Using customer-product-competitor analysis as drivers for a business' reconfiguration and market re-positioning

 

 

O Boniface

Department of Business Management: University of Johannesburg. boniokanga@gmail.com

 

 

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ABSTRACT

As businesses strive to reconfigure and modify their capabilities to remain sustainable, lack of clear strategic business platforms against which relevant strategic analysis can be based often affect the strategic decisions to reconfigure and modify their capabilities to respond to the emerging industry and market changes. This study seeks to deal with such a challenge by using confirmatory factor analysis to test and validate the null hypothesis that customer-product-competitor analysis offers critical interactive strategic business platforms that instigate a firm's decision to reconfigure, innovate and re-position itself to withstand all unfolding discontinuities.
As customer-product-competitor analysis aids assessment of the complexities of the existing, prospective and unbothered customers' needs, confirmatory factor analysis revealed improved understanding of customer-product-competitor dynamics to enable a firm assess its capabilities vis-á-vis rivals' capabilities to respond to the identified gaps. In case of imbalances offering rivals with superior advantages, such analysis spurs capabilities' reconfiguration and modifications to leverage a firm's market re-positioning to respond to such imbalances. Subsequently, this bolsters a firm's overall competitiveness and improved market performance.
In contrast to the approach in Kim and Mauborgne's new value innovation logic and Teece's dynamic capabilities theories in which such critical platforms are not clearly identified and explained, this study enriches the existing theories by suggesting customer-product-competitor analysis model that determines decisions to reconfigure and modify or not to do so to create new values that in turn spawn a firm's market re-positioning, continuity and sustainability.

Key phrases: business' reconfiguration; CFA - confirmatory factor analysis; CPC - customer-product-competitor analysis; market re-positioning

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1. INTRODUCTION

Business continuity and sustainability require constant capabilities' reconfiguration and market repositioning for a firm to thrive in the midst of the often-intense discontinuities in the modern business environment (Reeves, Love & Trillmanns 2015:3). Reconfiguration is a strategic business process of reviewing and improving a firm's capabilities and potential to deal with newly emerging industry and market scenarios (Reeves et al. 2015:3). Market repositioning aids review and abandonment of the old brand image associated with certain offerings in favour of a new image (Girneata 2014:8). Constant reconfiguration drives constant capabilities' modifications to improve the existing value offerings. It also aids the creation of new values to tap new opportunities emerging from the changes in customer tastes and preferences.

It is through reconfigurations and modifications of production capabilities that firms are often able to deliver superior values and undertake market repositioning to edify their continuity and sustainability (Girneata 2014:8). However, constant capabilities' reconfigurations and modifications require thorough business analysis and sensing of information about the unfolding or the impending changes in trends. Reactive and proactive sensing of the changes in trends bolster identification of a combination of strategically integrated business platforms that can be used to create new values that leverage a firm's market competitiveness, continuity and sustainability (Reeves & Deimler 2011:4).

To create values that leverage a firm's market competitiveness and sustainability, the analysis of customer needs and changes in trends are critical pedigrees of the foundational pillars that bolster the required capabilities' modifications to create new values (Grönroos & Voima 2012:49; Kyoichi & Arai 2010:10; Reeves & Deimler 2011:4).

However, a consensus seems to have not yet been reached among business leaders and scholars on the strategic business platforms of analysis that drive the identification of gaps, unfilled needs, operational inefficiencies and deficiencies vis-ä-vis those of rivals that must be addressed through new innovations to create new values (Altindag, Zehir & Acar 2010:18; Ambrosini, Bowman & Collier 2009:5; Argote & Ren 2012:137). It is such a contentious question that this research deals with by using confirmatory factor analysis to statistically and scientifically evaluate how customer-product-competitor analysis are the three interactive strategic business platforms that would drive a firm's reconfiguration and market re-positioning to leverage market competitiveness, continuity and sustainability in the midst of all protracted discontinuities.

 

2. LITERATURE REVIEW

Strategic business platforms are the domains of analysis in which the executives must concentrate to identify gaps, unfilled needs and deficiencies that must be addressed through reconfigurations and innovations to create new values (Reeves & Deimler 2011:4). It maps and tracks changes in customer needs and demands. This aids the evaluation and identification of new improvement measures that can be undertaken to create new values that leverage a firm's overall superior market performance. The essence for identification of critical strategic business platforms for new value innovations is accentuated in the constantly changing modern business environment that requires firms to identify and isolate the areas for new innovations and value creations (Bradley, Loucks, Macaulay Noronha & Wade 2015:9).

Continuous analysis, sensing and detecting of environmental changes therefore enable executives to continuously reconfigure the efficacy of their existing business approach, models, philosophies and marketing strategies (Warsta, Juntunen & Veikko 2015:3). It is through such reconfigurations and evaluations that businesses can reach logical conclusions on the extent to which their capabilities are well-positioned to optimise the prevailing opportunities whilst at the same time also diffusing the identified threats. However, the question as to the appropriate strategic business platforms of analysis that drive new value innovations seems yet a grey area that has not yet been widely explored by different authors.

In the evaluation of how to create new values, most authors either focus only on one or two strategic business platforms such as the market, customers, products or competitors as the basis for the identification of the gaps that must be filled through new innovations to improve a firm's overall competitiveness (Altindag et al. 2010:18; Ambrosini et al. 2009:5; Argote & Ren 2012:137). To address this conceptual limitation, this research draws the interpretation of different strategic management and marketing theories to fundamentally argue in Figure 1 that customer-product-competitor analysis constitutes the integrated three interactive strategic business platforms that drive a firm's reconfiguration and market re-positioning to subsequently leverage its market competitiveness, continuity and sustainability. It is the fundamental argument in the CPC framework of analysis that to thrive, it is critical that strategic business decisions are instigated by the results of the analysis of customer, product and competitor platforms.

 

 

2.1 Customer

It is often the motive of every business to not only aggressively protect its existing customer base, but also to continuously attract new customers either from the pool of the previously unbothered segments or from the rivals' customer base (Ballantyne, Frow, Varey & Payne 2011:202). Customer platform enhances analysis of the implications of the prevailing trends on the existing, prospective and the unbothered customers whose interests may still be aroused. In terms of the existing customers, businesses are usually concerned with the current levels of sales because it is through such sales that businesses can generate revenues that enable them to meet the existing overheads (Kyoichi & Arai 2010:10).

The capabilities of capabilities to meet the existing overheads eases tension associated with uncertainties that may emerge in the event of only limited sales as to how such a business would continue to thrive or survive. Hence, the evaluation of how the prevailing trends and changes are affecting the ability of the business to attract and retain most of its existing customers is often prioritised by the executives to gauge not only their present continuity, but also future sustainability (Grönroos & Voima 2012:49). Unfortunately, there is often a common tendency for the executives to focus on the existing customers as contrasted with the analysis of the needs of the prospective and the unbothered customer segments. This affects the extent to which businesses are able to undertake necessary changes to respond to the needs of all the customer segments.

Events that can affect the attraction and retention of the existing, prospective and the unbothered customers are often linked to the changes causing increment in the prices of inputs (Ballantyne et al. 2011:202). A rise in the prices of inputs due to regulatory changes or increment in competition for scarce resources can affect a firm's cost competitiveness.

Besides changes in the prices of inputs, poor marketing and commitment of the desired financial resources in marketing may also undermine a business' ability to attract and retain prospective customers and the customers from the unbothered segments. Such deficiencies usually cause a gap in the markets that can easily be utilised by competitors to infiltrate the market and use such gaps as a base for building further capabilities and competencies to attack and erode a business' competitiveness (Karakaya & Yannopoulos 2011:171). The use of customer platform for CPC analysis, therefore enables the executives identify unfilled customer needs to undertake the necessary modifications to fill such gaps. However, as threats to a business' customer base may arise from the shift and changes in customer preferences and demands for the competitors' products, the failure of the business to constantly modify the quality and features of its products can also limit its effective market performance and sustainability.

2.2 Product

Following the understanding of customer needs and demands, the analysis of the product platform edifies the evaluation and understanding of whether the quality and features of the existing products perfectly respond to the prevailing customer demands and needs. Products are services or goods offered by businesses (Broring & Cloutier 2008:96). Enhancing a product's effective responsiveness to the demands and needs of the customers often requires analysis and improvement of both the core and the augmented products. Core products refer to the extent to which the product being offered by the firm is capable of effectively serving the functions that it claims to perform (Protcko & Dornberger 2014:225; Vorhies & Bush 2011:736).

Capabilities of the product's core aspects to serve its desired functions influence improvement of customer perceptions. A product's fulfilment of its functionality edifies the extent to which the customer expectation of the product's functionality can match or exceed customer perception about the product after its consumption. However, it is still often critical that as the evaluation ensures the core aspects of the product are perfectly responsive to the demands and needs of the customers, the other initiative must be directed towards ensuring that augmented aspects of the product also perfectly match and meet customer expectations (Doug & Katz 2013:2).

Augmented products are features, attributes, designs, quality, packaging and modes of delivery that define and distinguish the product from those of rivals. Integrated approaches leveraging the capabilities of both the core and augmented aspects of the products to perfectly respond to the needs and demands of the consumers therefore edify the improvement of an enterprise's competitiveness (Harram & Fozia 2015:5).

However, as the executives evaluate the effectiveness of their products to respond to the demands and needs of the customers, it is also often of essence to continuously assess the existing gaps and the customer needs that have not been filled to devise the strategies through which such gaps can be filled. To bolster the effectiveness of the undertaken strategies, such analysis may have to be accompanied by the evaluation of the effectiveness of the business' products vis-à-vis the quality and attractiveness of rivals' products (Protcko & Dornberger 2014:225). Such analysis would require competitor analysis and interpretation of the implications of their unfolding actions on a firm's performance.

2.3 Competitor

Competitor analysis is a strategic process of gaining critical insights into how competitors' behaviours and probable intended motives can undermine or aid a firm's effective market performance (Vorhies & Bush 2011:736). In instances where competitor analysis signifies a firm's effective market performance may be undermined by competitors' behaviours and intended motives, competitor analysis often improves strategic decisions to counter such moves. It aids the evaluation of the strengths and weaknesses of the business vis-ä-vis those of its rivals (Ludwig & Pemberton 2011:215).

Competitor analysis does not only entail analysis and understanding of the unfolding rivals' behaviours, but also assessment of a firm's existing capabilities to match or exceed such unfolding volatile competition behaviours. It is through such analysis that businesses are able to identify areas of weaknesses and determine a combination of remedial strategic interventions to thwart such weaknesses or threats.

To assess and improve a firm's overall capabilities, areas for evaluation often encompass analysis of production capabilities, adequacy of the resources at a firm's disposal vis-à-vis the resources at the disposal of the competitors. In such analysis, it is also critical to evaluate skills and competencies, historical experience, and the consistency of the rivals' quality commitment and dedication to deliver superior values. It also entails evaluation of a firm's existing capabilities to perfectly match or exceed rivals' capabilities. If a firm finds itself lagging in certain key areas, it is often critical to devise such business strategies or models that can be used to improve or develop new capabilities that fill such gaps (Marvin, Shamir & Fernando 2014:6). Quite often, most keen executives also explore the extent to which the increasing proliferation of new entrants into the market may affect the sources of supplies' future sustainability (Karakaya & Yannopoulos 2011:171). This influences analysis of the magnitude of the impact of competition on the inputs' prices as well as the sources of supplies' future sustainability.

Avoidance of future risks of resource scarcity that may affect input costs and a firm's cost competitiveness may require either direct investment in the sources of supplies. It may require backward vertical integration through acquisitions or strategic alliances with the major input producers to lock out rivals from their sources of inputs. This secures the future sources of supplies. Other strategies would entail evaluating how new innovations can be undertaken to enhance optimisation of the existing sources of inputs. Although that signifies competitor analysis aids the determining of the retaliations that a firm can undertake, quite often, the undertaken reactionary strategic actions may depend on whether a firm operates in highly fragmented or concentrated industries.

In concentrated industries, consistency in tracking and understanding of the unfolding competitors' moves is often critical for undertaking critical counter strategies to improve a firm's survival in the often more relatively volatile and unpredictable concentrated markets. This contrasts with the strategic approach undertaken in highly fragmented markets or industries in which due to high variability of industry conditions, moves of each competitor may not necessarily attract a firm's retaliations. Conventionally, the motives of competitor analysis are usually to identify the major threatening competitors, their strategies, intended actions and how they may react to actions seeking to influence industry conditions and the overall game to a firm's advantage.

However, considering the pace at which the contemporary market and industry trends are changing as well as the speed at which rivals are acting, competitor analysis is no longer a reactionary strategic process. Instead, it is increasingly turning into a cognitive strategic sensing process requiring firms to analyse, sense, anticipate and undertake the required strategic actions before competitors act (Porter 1985:1). A firm's capabilities to sense, anticipate and undertake actions to thwart probable competitors' threats reside in the executives' capabilities to constantly track and understand rival's motives. Such analysis must be accompanied by the analysis of rivals' assumptions about the industry and market conditions, and their strategies and intangible and tangible capabilities to effect strategic actions necessary to achieve such strategic intents. Depending on the results of trends' analysis, some of the proactive strategies that firms often undertake to consolidate their positions are often associated with pre-entry defensive strategies encompassing signalling, fortifying, covering all bases, continuous improvement and capacity expansion (Porter 1979:4; Yannopoulos 2011:1; Yoffie & Kwak 2001:5).

Although such defensive and offensive strategies may leverage a firm's competitiveness, quite often, the sustainability of the undertaken defensive and offensive strategies are drawn from the extent to which the strategic value creating resources offering such advantages are largely inimitable, irreplaceable and substitutable. In line with the strategic logic in Barney's (1991) resource-based theory, a firm's strategic value creating resources are often rendered inimitable, irreplaceable and non-substitutable by virtue of some unique historical facts, experience and capabilities derived from newly less understood technologies.

However, considering the increasing advancement in knowledge generation, acquisition and utilisation, competitive investment in innovative initiatives often erodes inimitability, irreplaceability and non-substitutability of most of the strategic value creating resources. This places most of the industry players at equal footing (Barreto 2010:256). This suggests outmatching rivals and gaining the desired growth momentum would require firms to strive to gain first-mover advantages in markets or industries not yet largely recognised by most rivals. To gain first-mover advantages in such new markets or industries, firms have got to sense, anticipate and undertake immediate strategic actions to seize the unfolding new opportunities at a pace rivals are unable to do so.

However, a firm's ability to explore and identify new markets and industries from which to gain first-mover advantages may depend on the abandonment of the conventional strategic logic in favour of strategic value innovation logic (Kim & Mauborgne 2015). As contrasted to the conventional strategic logic, strategic value innovation logic requires firms to focus on creating new values to unlock new opportunities that render irrelevant the competition in the existing markets. New value innovations often require the application of ERIC (eliminate-reduce-increase-create) grid and buyer experience and utility map.

To create new values, ERIC Grid enhances identification of the values taken for granted by most of the industry players that must be eliminated or over-offered values that must be reduced. It may also require the identification and increment of the under-offered values or introduction of new values that had not been anticipated by most of the industry players. Quite often, the application of ERIC grid is undertaken in conjunction with the use of buyer experience and utility map to evaluate and understand new values that can be created to delight customer experience and satisfaction as they undergo the experience cycle of search, purchase, delivery, consumption and disposal.

In other words, these theories suggest competitor analysis in the increasingly more precarious contemporary business environment is not just a process of analysing and reacting to the prevailing and emerging competition trends, but a process entailing sensing, anticipating and undertaking immediate innovative strategic actions to stay ahead of competitors.

Against that backdrop, it is part of the fundamental reasoning in the null hypothesis in Figure 1 that effective customer-product-competitor analysis would leverage capabilities' reconfigurations and market re-positioning to bolster a firm's overall competitiveness and sustainability. Such modifications may entail review and improvement of production capabilities, new value innovations, advertisement and quality improvement strategies.

Quite often, such modifications leverage a firm's ability to effectively respond to customer needs and thwart competition. Implicitly, such a view seems supported in elucidation of the methodologies for undertaking blue ocean strategy that Kim and Mauborgne (2015) highlight to include ERIC Grid and the buyer experience and utility map. In the application of these methodologies, it is evident that although Kim and Mauborgne (2015) do not isolate customer-product-competitor analysis as the critical strategic business platforms for new value innovations, the interactive interplay between the evaluation of the changing customer needs and a product's responsiveness to such changing needs vis-à-vis attractiveness of the competitors' offerings is still evidently a critical prerequisite for the application of the ERIC Grid.

Except that as the ERIC Grid is being applied to assess and identify factors that must be eliminated, reduced, increased or created, it tends to focus on the analysis of the industry practices and competitors rather than the customers or the products. Buyer experience and utility map examine customer experience and usage of the products vis-à-vis the capabilities of the firm to deliver on such needs. The logical evaluation of Kim and Mauborgne's (2015) concept of new value innovations would therefore certainly suggest that the process of new value innovations is strongly anchored on the interactive evaluation of customer, product and competitor platforms.

However, the essence of the application of such integrated three interactive strategic business platforms still do not emerge clearly for most businesses to easily replicate. Even if the importance for the evaluation of the organisation, customer, suppliers, intermediaries, market and competitors are well reiterated in micro-environmental analysis theories, it still ignores the essence for analysis of product analysis as one of the critical business platforms (Barrales-Molina & Perez-Arostegui 2010:135; Durmaz & lhan 2015:210).

At the same time, strategic scenario analysis tools and techniques such as PESTEL (political, economical, social, technological, ecological & legal) analysis, SWOT (strength, weaknesses, opportunities & threats) analysis, forecasting, and Porter's (1985) four corners' (motives, strategy, assumptions and capabilities) analysis facilitate the understanding of the unfolding events and the reactions that the firm can undertake.

However, they are still often less effective for the identification of the specific business activities that businesses must accomplish to create new values that perfectly respond to the changes in customer demands and preferences. In other words, if the other strategic management tools of analysis such as PESTEL and SWOT analysis are to produce the desired business results on value creations, the process of analysis must subsequently narrow down to customer, product and competitors' analysis.

It is on that basis that this research crafts the CPC's (customer, product and competitor) three platforms of analysis for reconfigurations and new value innovations in Figure 1 to offer specific three strategic business platforms that businesses can replicate in conjunction with the other strategic management tools to obtain specific results that can enable them identify the specific strategic responses that can be undertaken. The rationale for CPC framework of analysis is latent in its simplicity and ease of use for businesses to gain quick understanding of the implications of the prevailing trends on their customers, products and competitiveness. In other words, the essence for the development and application of CPC's three interactive platforms for new value innovations is motivated by the problem enunciated in the next section.

 

3. PROBLEM INVESTIGATED

Lack of clearly designated strategic business platforms for new value innovations affects the identification of new gaps and unfilled needs that must be addressed to create new values that leverage a business' competitiveness, continuity and sustainability in the midst of all discontinuities and unpredictabilities.

 

4. RESEARCH OBJECTIVE

This research aims to test and validate how the use of customer-product-competitor analysis (CPC) model in Figure 1 would drive business capabilities' reconfiguration and market repositioning to leverage its market competitiveness, continuity and sustainability in the midst of all protracted discontinuities.

 

5. RESEARCH HYPOTHESIS

The null hypothesis is reflected in Figure 1 that effective customer-product-competitor analysis would leverage capabilities' reconfigurations and market re-positioning to bolster a firm's overall competitiveness and sustainability.

 

6. METHODOLOGY

Confirmatory factor analysis was undertaken to assess whether all the latent constructs and their associated measuring variables are statistically significant to confirm the null hypothesis in Figure 1 that customer-product-competitor analysis aids the reconfiguration of a firm's capabilities and market repositioning (Brown 2006:16; Unkel 2015:3). To accomplish this, confirmatory factor analysis entailed the application of four main steps encompassing model specification, sample size estimation, data collection, calculation of estimates and interpretation.

With the latent constructs and the associated measuring variables specified in Figure 1, the process of sample size estimation was accomplished basing on the rule of thumb articulated by Hair, Black, Babin and Anderson (2010:94) that a sample size of 50 respondents and above is statistically valid for assessing whether the observed sample covariance matrix matches SEM's estimated covariance matrix. Drawing from such interpretation, this research used a sample size of 141 respondents drawn from a cross section of 20 different businesses constituting of both large and medium size manufacturing businesses in Gauteng and Kwa-Zulu Natal Provinces.

Data collection was accomplished using a five point Likert-style questionnaire (strongly disagree-1, disagree-2, unsure-3, agree-4 & strongly agree-5) that contained four main sections aligned to the four constructs in Figure 1 that include customer, product and, competitor platforms, and the effects of CPC analysis on capabilities' reconfigurations and market repositioning. A Cronbach alpha's analysis was 0.7 and was interpreted to imply content validity and reliability of the measuring instrument. In the calculation of estimates and interpretation of indices, standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²) were used in conjunction with absolute fit indices, incremental fit indices and parsimony adjusted measures to assess whether the observed sample covariance matrix matches the SEM estimate covariance matrix in Figure 1.

Regarding the results of standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²), The reasoning in the theory of Bollen and Davis (2009:536) was used to assess whether all variables load at + 0.50 with a variance of 30% for squared multiple correlation coefficient (r²) to conclude that the indicators are statistically significant to explain the validity of the model in Figure 1. All these were accompanied by the application of absolute fit indices that included chi-squared (x²) analysis, RMSEA-root mean square error of approximation and GFI-goodness of fitness index.

For chi-squared (x²) analysis, Hair et al.'s (2010:94) reasoning that the observed sample covariance matrix does not match the SEM estimated covariance matrix if chi-squared (x²) p-value < 0.05 as contrasted to when chi-squared (x²) p-value > .05 was used in the analysis of the overall fitness of the model.

Whereas the interpretation of the results of RMSEA was based on Bollen and Davis' (2009:536) argument that a model perfectly reproduces the observed sample data if RMSEA < 0.08 with PCIose> 0.05), the level of acceptance for goodness of fitness index was GFI > 0.90. The incremental fit indices that were used included AGFI-adjusted goodness of fitness index, CFI-comparative fit index, TLI- Tucker Lewis index, NFI - normed fit index, and RMR-root mean residual. Using Hair et al.'s (2010:94) interpretation, AGFI, CFI, TLI and NFI falling in the range of 0 and 1 indicated good model fitness just as RMR that falls between - 4.0 and +4.0. The application of parsimonious adjusted measures entailed the evaluation of whether CMIN (chi-squared (x²) / df- (degree of freedom) had a score of CMIN/df< 3. The details of the findings are as presented and discussed in the next sections.

 

7. FINDINGS

To assess whether CFA findings confirmed the null hypothesis in Figure 1 that basing business analysis on customer-product-competitor analysis aids the reconfiguration of a firm's capabilities and market repositioning to improve a business' continuity and sustainability, the results of confirmatory factor analysis were presented and discussed according to two subheadings encompassing:

■ standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²);

■ absolute fit indices, incremental fit indices and parsimonious adjusted measures. The details are evaluated as follows.

7.1 Standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²)

The argument in Figure 1 that basing business analysis on customer-product-competitor analysis aids the reconfiguration of a firm's capabilities and market repositioning to improve a business' continuity and sustainability seems accentuated in the results of standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²) in Table 1 and Figure 2. It is evident in Table 1 and Figure 2 that whereas the existing customers (EC) had a factor loading of 0.81 and prospective customers (PC) loaded at 53 onto customers as the measuring construct, loadings for unbothered customer segments (UC) and rivals' loyal customers (RLC) were 0.51 and 0.63 respectively. Such a finding seems to echo Bollen and Davis' (2009:536) reasoning that indicators are statistically significant to explain the validity of the model if factor loadings are + 0.50 with a variance of 30% for squared multiple correlation coefficient (r²). These findings imply that the analysis of the needs and demands of the existing, prospective, unbothered and rivals' loyal customers improves the executives understanding of market dynamics. Subsequently, this aids conceptualisation and application of the appropriate product and market strategies to attract and retain new customers whilst also striving to retain the existing ones.

 

 

 

 

Yet, while also using Bollen and Davis' (2009:536) rule of thumb of a variance of 30% as indicating significance of indicator errors, the analysis and interpretation of squared multiple correlation coefficients in Table 2 and Figure 2 would also suggest that existing customers (EC) was significantly explained by 66% of the variance in the common factor. In other words, the fact that all the variables for customer as one of the strategic business platforms were significantly explained by the variance in customer as a common factor is reflected in the fact that prospective customers (PC) was also explained by 28% of the variance in the common factor, as the unbothered customer segments (UC) and rivals' loyal customers (RLC) were respectively explained by 26% and 40% of the variance in the common factor. In the context of Hair et al.'s (2010) reasoning and Bollen and Davis' (2009:536) rule of thumb, it can be argued that findings suggest customer analysis as part of the three interactive strategic business platforms encompassing customer, product and competitor analysis to influence the determining of an enterprise's reconfigurations and modifications that must be undertaken.

 

 

Such reconfigurations and modifications enhance the creation of new values to not only reposition the enterprise, but also to improve the enterprise's sustainability by responding to the emerging new unfilled customer needs. However, to accomplish that, the results of confirmatory factor analysis imply that it is not only the understanding of the needs of the existing customers which is critical, but also the needs and demands of the prospective customers, the unbothered customer segments and rivals' loyal customers.

The understanding of such different categories of customer needs edifies the determining of the critical strategies that must be undertaken to satisfy and retain the existing customers, whilst at the same time also attracting and arousing the interests of the often-unbothered customers.

It is often through such a strategy that enterprises are able to weaken rivals' market base and erode competitors' market share to subsequently gain competitive edge over rivals. To achieve such strategic objectives, confirmatory factor analysis indicates that the evaluation of customer platforms must be accompanied by effective evaluation of product as one of the other critical platforms for new value innovations. This is accentuated in the fact that Figure 2 highlights the co-relationship between customer analysis and product analysis to be statistically significant at 1.

Figure 2 also spotlights the co-relationship between customer analysis and reconfiguration to be statistically significant at -1. Scores of 1 and -1 are certainly within Jasper's (2010:104) interpretation that with a score falling within the range of + 0 and 1, a relationship between two variables or constructs can be construed to be statistically significant. In that context, it can be interpreted that the analysis of customer platform enhances the understanding of customer of needs and demands to assess the product modifications or even new products that must be developed to respond to such needs.

Likewise, the evaluation of product platform goes hand in hand with the evaluation of customer needs and demands so that if a product or its feature is not desired by the customers, it can be dropped in favour of the products that customers prefer. Besides the statistically significant co-relationship between customer and product platforms, it is also reiterated in Table 1 and Figure 2 that effective product analysis as a second platform of new value innovations is often predicted by effective evaluation of the products' core functions, performance, quality, features and design.

Using the illustrations in Table 1 and Figure 2, it can be noted that using Hair et al.'s (2010) rule of thumb of + 0.50, all these variables significantly loaded on product as a measuring construct in the CPC model in Figure 1. Besides product quality (PQ) with a loading of 0.54 and features and design (FD) that loaded at 0.77, Table 1 and Figure 2 imply that core functions (CF) loaded at 0.62 , as performance (P) that loaded at 0.78 was also found to be statistically significant.

The view that product's functionality and performance are at the core of the overall analysis of product as one of the platforms for new value innovations is also substantiated in the results of squared multiple correlation coefficients (r²) in Table 2 and Figure 2.

Table 2 and Figure 2 reiterate CF (core functions) was explained by 39% of the variance in the common factor. The same was also noted to apply to P (performance) which is indicated to have been explained by 60% of the variance in the common factor, just as product quality (PQ) that had 30% and features and design (FD) which was explained by 60% of the variance in the common factor (product platform).

Using Bollen and Davis' (2009:536) rule of thumb of a variance of 30% as indicating significance of indicator errors, it can be argued that the effectiveness of product analysis is predicted by its core functions, performance, quality, features and design. This edifies a firm's responsiveness to customer needs and demands. Though effective analysis of product platform in conjunction with the evaluation of the competitiveness' of rivals' products would also facilitate relevant reconfigurations and modifications to create new values and thwart competition threats.

Such a view is consonant with the reiteration in Figure 2 that signifies the co-relationship between product and competitor analysis to be statistically significant at .96. As on the other hand, the co-relationship between product analysis and reconfigurations was statistically significant at 1. This suggests product analysis that involves a comparative analysis and benchmarking of a firm's products with rivals' products enables firms reconfigure themselves to not only undertake modifications, but also new value innovations to outwit the identified sources of threats. It was not only product analysis that emerged significant, but also competitor analysis as the last construct of CPC analysis.

Results of confirmatory factor analysis in Figure 2 and Table 1 indicated competitor analysis to be predicted by the evaluation of a firm's production capabilities (MPC) that had a factor loading of 0.74, historical experience (HE) that loaded at 0.62, and subsequently quality consistency (QC) with a loading of 0.60, and resources (R) that had a loading of 0.66.

The significance of these variables was also bolstered by the results of squared multiple co-relations co-efficient that indicated a firm's production capabilities (FPC) to be explained by 55% of the variance in the common factor, as resources (R) scored 44%. Squared multiple co-relations co-efficient also indicated historical experience (HE) and quality consistency (QC) respectively were explained by 36% and 39% of the variance in the common factor. A fact which in the context of Bollen and Davis' (2009:536) rule of thumb of + 30% implies all the variables were significantly explained by the variances in the common factor.

In terms of the results of co-relation analysis, competitor analysis was also found to directly influence a firm's reconfigurations for new value innovations to be undertaken on the basis that the co-relationship between competitor analysis and reconfigurations was statistically significant at 1.

As co-relationship between competitors' analysis with product analysis was also significant at 0.96, just as the co-relationship between competitors' analysis with customer analysis that loaded at 1.

This implies the analysis and benchmarking that a firm undertakes with its competitors seem to only impact a firm's reconfigurations and new value innovations through the analysis and recognition of the changes in customer needs and product modifications. It is such changes that often instigate the need for a firm's reconfiguration to support new modifications and values to be created.

It is certainly therefore apparent from the results of CFA that the evaluation of a firm's production capabilities, historical experience and quality consistency vis-ä-vis those of the competitors enhances the ability of the executives to understand their weaknesses and strengths. This edifies necessary capabilities' reconfigurations and modifications that must be undertaken to create new values and thwart competition.

Such a view is echoed in the results that the overall effectiveness of CPC's (customer-product-competitors) three platforms' analysis predicts the reconfiguration of a firm's capabilities, and its market repositioning. Marketing repositioning is attained by the modification of operational and production capabilities that loads at 0.57 and 0.66 respectively.

Market repositioning was also found to be attained through new value innovations (NVI) with a loading of 0.57, advertisement and marketing (AM) that loaded at 0.58, and quality improvement (Ql) with a loading of 0.70.

At the same time, the results of squared multiple co-relation coefficients revealed modification of operational capabilities (OC) was explained by 32% of the variance in the common factor. As production capabilities (MPC) was explained by 44% of the variance in the common factor, and new value innovations (NVI) by 32% of the variance in the common factor. Advertisement and marketing (AM) as well as quality improvement (Ql) were respectively explained by 34% and 39% of the variance in the common factor.

In other words, the results of standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²) seem strongly supported in the results of incremental fit indices, but not in the results of absolute fit indices and parsimonious adjusted measures.

7.2 Absolute fit indices, incrementai fit indices and parsimonious adjusted measures

In line with the illustration in Table 3, the absolute fit indices used in the analysis of the overall fitness of the model included chi-squared (x²) analysis, RMSEA-root mean square error of approximation and GFI-goodness of fitness index. However, none of the absolute fit indices indicated good model fitness. In terms of chi-squared (x²) analysis, Table 3 reiterates the results were chi-squared (x²) = 324.582 (df=53, p-value = 0.000).

 

 

Drawing from Hair et al.'s (2010:94) interpretation, the observed sample covariance matrix does not match the SEM estimated covariance matrix if chi-squared (x²) p-value < 0.05 as contrasted to when chi-squared (x²) p-value > 0.05. In line with the illustration in Table 3, chi-squared (x²) = 324.582 (df = 53, p-value = 0.000 < 0.05) therefore implies that the observed sample covariance matrix does not perfectly reflect the SEM estimated covariance matrix in Figure 1.

The results of chi-squared (x²) = 324.582 (df=53, p-value = 0.000 < 0.05) does not support the null hypothesis in Figure 1 that customer-product and competitor analysis enables executives identify the need to reconfigure their capabilities to create new values and respond to emerging new customer needs and competition threats.

Lack of model fitness was also indicated in the results of RMSEA-root mean square error of approximation which as indicated in Table 3 is 0.2. Since Bollen and Davis (2009:536) argue that a model perfectly reproduces the observed sample data if RMSEA < 0.08 with PCIose> 0.05), it can be interpreted that with Table 3 indicating RMSEA= 0.2 > 0.08, the model in Figure 1 cannot be accepted.

RMSEA= 0.2 > 0.08 does not support the ratiocination in the null hypothesis in Figure 1 that the use of customer-product-competitor analysis edifies necessary reconfigurations to create new values to leverage a business' overall continuity and sustainability. Although lack of model fitness was also echoed in the results of GFI-goodness of fitness index (Level of Acceptance-GFI > 0.90) which was GFI = 0.7 < 0.90, it is critical to note that generally, absolute fit indices tend to use very stringent measures in the assessment of model fitness.

Since some of the absolute fit indices such as chi-squared (x²) are also influenced by sample sizes used in the study, the implications are often latent in the fact that over reliance on such stringent measures can easily cause a statistical type 11 error which is the risks of rejecting a true null proposition that should have been accepted.

Such a view is substantiated in the fact that with most of the results of standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²) indicating most of the variables to significantly load onto their associated latent constructs, the results of absolute fit indices that indicate lack of model fitness cannot easily be relied on to reject the null hypothesis in Figure 1.

Instead, the results of standardised regression weights (factor loadings) and squared multiple correlation coefficients (r²) seem to corroborate the results of most of the incremental fit indices that indicate good model fitness. Whereas AGFI-adjusted goodness of fitness index had a score of 0.6 and CFI-comparative fit index scored 0.2, as TLI- Tucker Lewis index and NFI-Normed fit index had scores of 0.03 and 0.2 respectively, RMR-root mean residual scored 0.7.

Using Hair et al.'s (2010:94) interpretation, AGFI, CFI, TLI and NFI falling in the range of 0 and 1 indicate good model fitness just as RMR that falls between -4.0 and +4.0. Such interpretation suggests that the results of AGFI, CFI, TLI, NFI and RMR support the null hypothesis in Figure 1 that customer-product-competitor analysis edifies necessary reconfigurations to create new values to improve a firm's overall continuity and sustainability. As on the other hand, the results of parsimonious adjusted measures using CMIN/df of 6.1 exceed the ratio of 1 to 3 which is used for assessing model fitness. However, the overall interpretation of the results of confirmatory factor analysis seems to echo the ratiocination in the null hypothesis in Figure 1 that customer-product-competitor analysis in the CPC model in Figure 1 edifies necessary reconfigurations to create new values that subsequently leverage a firm's overall continuity and sustainability.

 

8. DISCUSSION

In the increasingly competitive and discontinuous modern business environment, constant change instigated by constant changes and evolutions in customer tastes and preferences and new innovations by rivals reshape industry conditions (Protcko & Dornberger 2014:225; Vorhies & Bush 2011:736). Such changes cause discontinuities, evolutions and changes in market conditions that affect a firm's sustainability. In effect, ensuring the sustainability of the enterprise does not only require executives to anticipate and wait to react to the emerging changes. Instead, intense customer, product and competitor analysis is of essence for businesses to easily sense whether they are perfectly responding to the needs of their customers.

CPC analysis enables enterprises evaluate not only the extent to which their business approaches, models and philosophies are aligned and responsive to the market needs, but also the diagnosis of the extent to which the products that they are offering perfectly match the needs and demands of the customers. It offers platforms for enterprises to evaluate and compare their capabilities with those of the rivals. It is such analysis that instigates either the need to maintain the status quo or for change to adapt and remain sustainable. Despite edifying the capabilities to react to the emerging new de-stabilising trends, through CPC analysis, executives can sense and anticipate the necessary changes and reconfigurations that must be undertaken to change and transform the enterprise to remain sustainable.

Such changes and reconfigurations may entail modification of the existing capabilities or investments in new capabilities to either match or surpass rivals' capabilities. It may also involve undertaking aggressive quality improvement initiatives, and the improvement of the existing value offerings and new value innovations to improve a firm's superior market performance. To effectively develop and apply CPC's three platforms of new value innovations, the results of confirmatory factor analysis would however raise several implications for the contemporary business managers.

 

9. MANAGERIAL IMPLICATIONS

For the contemporary business executives to effectively use CPC analysis to create new values and improve the sustainability of their businesses, it is indicated in the dynamic curve of CPC analysis in Figure 3 that in terms of customer analysis, the executives will have to divide the process of analysis according to the existing, prospective, unbothered and rivals' loyal customer domains. Effective use of these four domains would facilitate a firm's ability to not only apply strategies that contribute to the satisfaction and retention of the existing customers, but also the attraction and retention of either the previously unbothered customer segments or the existing competitors' loyal customers.

 

 

Each of these four domains is probed using certain specific questions. To facilitate the understanding of whether the firm is effectively responding to the needs of its existing customers or if there is a new gradual shift in customer tastes and preferences that the firm has not yet recognised, the firm should assess whether using their present business approach and philosophies, they are effectively responding to the needs and demands of the existing customers.

As such evaluations are being undertaken; the firm will also need to evaluate not only how to attract and retain the interested prospective customers, but also how to arouse the interest of the unbothered and the rivals' loyal customers.

That implies despite the essence of extensive marketing that target new customer segments, the introduction of new product offerings that target new customer segments is also often the critical required accompanying strategy. However, the evaluation of customer platform for new value innovations must also be undertaken in conjunction with product analysis.

The assessment of whether as compared to the rivals' products, the existing products are effectively meeting the needs of the market may require the executives to evaluate whether customer perceptions about a product's core functions vis-ä-vis those of rivals.

As such analysis is being undertaken, marketing executives may also have to assess customer perception about the capabilities, qualities, features and designs of the products as contrasted with the rivals' products.

At the same time, the assessment of a firm's production capabilities, financial resources at its disposal, skills and competencies, experience and quality consistencies vis-ä-vis those of the competitors may also need to be accompanied by the analysis of the necessary reconfigurations and modifications that must be undertaken to build new capabilities. Such improved capabilities must not only respond to customer needs, but also create new values to thwart competition. In other words, it is argued in Figure 3 that through the analysis of the three platforms for new value innovations, firms can identify unfilled customer needs, gaps and sense the needs for change and transformation to ensure business continuity and sustainability.

 

10. CONCLUSION

Business continuity and sustainability are strategic business states that every business aspires to achieve. Aspirations to achieve such a state are often accompanied by investment in superior technologies, aggressive marketing and advertisements as well as constant analysis and scanning of the macro-economic business environment. It is also often accompanied by the commitment of enormous funds in research and development, but with little utilisation of the three platforms for new value innovations to enhance the identification and tracking of the changes in customer needs and demands.

It is also often undertaken in conjunction with sensing and identification of the deficiencis of a business' existing products and capabilities as compared to those of rivals. However, through the suggestion of the business model in Figure 3, this study sought to fill such a gap by highlighting the critical business values that the application of the three interactive strategic business platforms encompassing customer-product-competitor analysis contributes towards eliciting critical information.

Quite often, such information guides strategic decisions on new investments that must be undertaken to improve a firm's capabilities to create new values and gain continuity and sustainability. The CPC model in Figure 3 was validated and refined through the responses from the business community and can therefore be recommended to contemporary managers as an improved model for new value innovations to improve business continuity. However, despite the comprehensive approach undertaken in Figure 3, future research can still explore the key success factors that influence effective use of such a model.

 

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