Purpose This study aims to analyze the available literature on the use of digital marketing in a business-to-business (B2B) context. It identifies gaps in the current research knowledge and proposes a research agenda for scholars and practitioners. Design/methodology/approach A systematic literature review has been conducted on B2B digital marketing. The various themes have been identified on the basis of the comprehensive analysis of extant literature. Also, semi-structured interviews with B2B marketing experts were also conducted to further refine the emerged digital marketing themes. Findings Although some B2B firms use digital marketing, most are unable to leverage its full benefits because of the dearth of comprehensive research on the subject. This review provides an insight into the emerging themes by developing a collaborative conceptual framework. The review highlights that few areas such as digital marketing communication and sales management have witnessed steady development while decision support systems, critical success factors, electronic marketing orientation (EMO), etc., were lesser explored. Furthermore, it identifies research gaps and highlights the emerging research themes for future researchers. Practical implications The collaborative framework will help organizations to align their digital marketing activities as per the changing market dynamics such as the focus on building social media capability, EMO and value co-creation. Originality/value Research on the use of digital marketing by B2B firms is still at the embryonic stage. This study is a pioneering effort to review the use of digital marketing in B2B organizations and identify research priorities for scholars and practitioners.
String matching is a problem where a pattern is to be searched within a text. In this paper, we study about selected string matching algorithms which compute shifts; based on good suffix rule and/or bad character rule or their variations. Algorithms are compared on the basis of their execution time for different data sets; those differ on patterns and alphabet sizes. Finally, we present a summary for the selection of these algorithms in different applications, based on the experimental results obtained. Good Suffix:Rule says if a mismatch occurs between the character 'a' of the pattern X and the character 'b' of the text Y during an attempt at position 'j' in Y. Then the already matched set of characters is considered as a suffix. The good-suffix shift consists in aligning this suffix with its rightmost occurrence in X that is preceded by a character different from character at position j. If there exists no such segment, the shift consists in aligning the longest set of characters in the suffix in Y with a matching prefix of X. Else shift the pattern ahead of suffix. Bad character:The bad-character shift consists in aligning the mismatched text character 'b' in Y with its rightmost occurrence in X. If 'b' does not occur in the pattern X, no occurrence of X in Y can include 'b', then the left end of the window is aligned with the character immediately after b. Selected Algorithms Boyer Moore Algorithm [1][2]:The algorithm scans the characters of the pattern from right to left beginning with the rightmost one. In case of a mismatch (or a complete match of the whole pattern) it uses two precomputed functions to shift the window to the right. These two shift functions are called the good-suffix shift (also called matching shift and the badcharacter shift (also called the occurrence shift). Maximum of the two rules is taken and patterns is shifted accordingly. Turbo Boyer Moore [3]: The Turbo-BM algorithm is an amelioration of the Boyer-Moore algorithm. It needs no extra preprocessing and requires only a constant extra space with respect to the original Boyer-Moore algorithm. It improves the worst-case complexity of Boyer-Moore algorithm. Zhu Takoaka [4]: Zhu and Takaoka designed an algorithm which performs the shift by considering the bad-character shift for two consecutive text characters. It simply modifies the Bad character rule employed in Boyer Moore, to consider two characters in case of mismatch.
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