DATOS DEL PRODUCTOR Y ESPECIFICACIONES Producto A.

As recommended by Lipsey and Wilson (2001), the selection of studies was performed so as to ensure that only relevant studies were incorporated.

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Studies were considered suitable for inclusion if they satisfied the following criteria:

1) Studies must report effect sizes for the PIC–firm performance relationship, and size of the firm samples examined.

2) Studies must measure constructs at the firm-level (and not product or product-line levels). This criterion ensures uniformity of data, and identical level of analysis (Hunter & Schmidt, 1990).

3) Studies must be independent from each other. This criterion implies that the studies should have investigated independent firm samples for reporting an effect size metric (Lipsey & Wilson, 2001).

4) The studies must be published after 01.01.1990 for inclusion, and deploy effects measures for operationalising PIC. The year chosen (1990) coincides with the emergence of DC Theory (see bibliometric review by Vogel & Güttel, 2013). This also spans a period of time consistent with several other meta-analytic reviews (e.g., see Crook et al., 2011; Joshi & Roh, 2009; Liang et al., 2010).

Consequent to the assessment of studies against the incorporation criteria, 169 studies from 226 identified were not included due to reasons, such as, the measures for PIC (and overlapping constructs) in the studies were not in correspondence with the effects measures adopted in the current study. This was important to ensure that effects measures were not confounded with resource-input measures and that PIC operationalisation was consistent across incorporated studies.

An important decision in data collection concerns the critical mass or minimum number of studies that must be included to enable a meaningful data-analysis. Although there are no heuristics to determine the optimal number of studies to be included in a meta-analysis, researchers often

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endeavour to collect the maximum possible numbers to enhance the statistical power of the analysis (e.g., see Kirca et al., 2011; Kirca et al., 2005). Thus, for the current study, 57 studies (representing 58 independent firm samples) were procured and the total number of effect sizes reported in the incorporated studies was 81. The sum of the sample sizes examined in all the

incorporated studies was 13,911firms.

Several considerations, such as the nature of primary studies, the effect size metric, time and resource constraints and research objectives, determine study numbers (Lipsey & Wilson, 2001). It was observed that the number of studies incorporated in meta-analyses (in management) can vary considerably. For instance, Li and Cropanzano (2009) include 12 studies, whereas Zablah et al. (2012) include 291 studies. After an extensive review, it was observed that a large majority of meta-analyses conducted in areas such as innovation, marketing and strategic management incorporate studies that number between 20 and 60 (see Appendix-3). The mode and the median of study numbers in these meta-analyses are 46 and 39 studies respectively.

Rosenbusch et al. (2011) affirm that the synthesis of 42 studies in their meta-

analysis was sufficient for a meta-analytic assessment. In support of the adequacy of 42 studies for examining the innovation and firm performance association, Rosenbusch et al. (2011: 448) state that (the number of collected

studies) ―represent a strong empirical base for a meta-analysis‖. Study

numbers in the vicinity of 42 studies, as in Rosenbusch et al. (2011), have been synthesised most frequently, as shown in Appendix-3. For example, 47 studies were aggregated in Brinckmann et al. (2010); 48 in Read et al. (2009); 39 in both Joshi and Roh (2009) and Leuschner et al. (2013), and 50 in a recent meta-analysis conducted by Verma, Sharma and Sheth (2015). In keeping with the numbers of studies aggregated in previous meta-analyses, a synthesis of studies in the neighbourhood of the median (i.e., 39 studies) was deemed sufficient for the current meta-analysis. Nevertheless, intensive efforts that yielded 57 studies were undertaken to obtain a greater number of studies than the median, in order to enhance the statistical power of the analysis.

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The inclusion rate of studies in the current meta-analysis is 25.22 percent (i.e., 57 studies out of the 226 studies examined) which is less than the inclusion rate observed for most meta-analyses (e.g., Grinstein, 2008b; Kirca et al., 2005; Stam et al., 2014). The inclusion rate was computed as the number of studies synthesised in the meta-analysis expressed as a percentage of the number of studies examined. Table 4.3 presents the inclusion rate for several meta-analyses conducted in fields such as marketing, strategic management, innovation and organisational behaviour. The data in the Table suggest that generally, between two-fifths (40%) to three-fourths (75%) of the total studies accumulated via manual and electronic (online databases) search are expected to yield usable effect sizes for inclusion.

The low inclusion rate in the current study can be largely ascribed to the very selective approach that stipulated inclusion of effect sizes based solely on effects measures of PIC. A considerable number of studies operationalising PIC (and overlapping constructs) were observed to employ resource input measures. Such studies constituted a substantial proportion (approximately one-half) of the total number of studies examined, and were excluded from the dataset. Only the studies using effects measures (alongside other relevant PIC measures as discussed in Chapter-2) were incorporated for analysis.

Table 4.3: Study inclusion rates

Study [Author(s), year] Inclusion rates

Brinckmann et al. (2010) 39% Brown and Peterson (1993) 66% Grinstein (2008b) 71% Henard and Szymanski (2001) 59% Joshi and Roh (2009) 41% Kirca et al. (2005) 61% Leuschner et al. (2013) 75% Stam et al. (2014) 40% Szymanski et al. (1993) 63%

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Some studies (e.g., Li & Atuahene-Gima, 2002) were not incorporated as they examined the same firm sample as other publications by the same authors. This ensured that the same firm sample was not considered more than once in the meta-analysis, thereby eliminating over-representation. By contrast, a single study, namely, Lööf and Heshmati (2006), reported effect sizes for two separate firm samples. Thus, two usable effect sizes (i.e., one effect size for each sample) could be extracted from this single study.

A few studies that were prima facie useful could not be coded as they were in

language other than English. For example, a study by Lavia, Otero, Olazaran and Albizu (2011) has been published in Spanish. Due to the constraints of time and high financial expense involved in engaging the services of a professional translator, such studies were dropped from consideration. This constraint has been highlighted in other meta-analyses as well, and these meta-analyses also incorporated studies published only in English (e.g., Damanpour, 1991; 1992). A description of the coding for studies meeting the incorporation criteria is presented next.